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Understanding Data Presentations (Guide + Examples)

In this age of overwhelming information, the skill to effectively convey data has become extremely valuable. Initiating a discussion on data presentation types involves thoughtful consideration of the nature of your data and the message you aim to convey. Different types of visualizations serve distinct purposes. Whether you’re dealing with how to develop a report or simply trying to communicate complex information, how you present data influences how well your audience understands and engages with it. This extensive guide leads you through the different ways of data presentation.

Table of Contents

What is a Data Presentation?

What should a data presentation include, line graphs, treemap chart, scatter plot, how to choose a data presentation type, recommended data presentation templates, common mistakes done in data presentation.

A data presentation is a slide deck that aims to disclose quantitative information to an audience through the use of visual formats and narrative techniques derived from data analysis, making complex data understandable and actionable. This process requires a series of tools, such as charts, graphs, tables, infographics, dashboards, and so on, supported by concise textual explanations to improve understanding and boost retention rate.

Data presentations require us to cull data in a format that allows the presenter to highlight trends, patterns, and insights so that the audience can act upon the shared information. In a few words, the goal of data presentations is to enable viewers to grasp complicated concepts or trends quickly, facilitating informed decision-making or deeper analysis.

Data presentations go beyond the mere usage of graphical elements. Seasoned presenters encompass visuals with the art of data storytelling , so the speech skillfully connects the points through a narrative that resonates with the audience. Depending on the purpose – inspire, persuade, inform, support decision-making processes, etc. – is the data presentation format that is better suited to help us in this journey.

To nail your upcoming data presentation, ensure to count with the following elements:

• Clear Objectives: Understand the intent of your presentation before selecting the graphical layout and metaphors to make content easier to grasp.
• Engaging introduction: Use a powerful hook from the get-go. For instance, you can ask a big question or present a problem that your data will answer. Take a look at our guide on how to start a presentation for tips & insights.
• Structured Narrative: Your data presentation must tell a coherent story. This means a beginning where you present the context, a middle section in which you present the data, and an ending that uses a call-to-action. Check our guide on presentation structure for further information.
• Visual Elements: These are the charts, graphs, and other elements of visual communication we ought to use to present data. This article will cover one by one the different types of data representation methods we can use, and provide further guidance on choosing between them.
• Insights and Analysis: This is not just showcasing a graph and letting people get an idea about it. A proper data presentation includes the interpretation of that data, the reason why it’s included, and why it matters to your research.
• Conclusion & CTA: Ending your presentation with a call to action is necessary. Whether you intend to wow your audience into acquiring your services, inspire them to change the world, or whatever the purpose of your presentation, there must be a stage in which you convey all that you shared and show the path to staying in touch. Plan ahead whether you want to use a thank-you slide, a video presentation, or which method is apt and tailored to the kind of presentation you deliver.
• Q&A Session: After your speech is concluded, allocate 3-5 minutes for the audience to raise any questions about the information you disclosed. This is an extra chance to establish your authority on the topic. Check our guide on questions and answer sessions in presentations here.

Bar charts are a graphical representation of data using rectangular bars to show quantities or frequencies in an established category. They make it easy for readers to spot patterns or trends. Bar charts can be horizontal or vertical, although the vertical format is commonly known as a column chart. They display categorical, discrete, or continuous variables grouped in class intervals [1] . They include an axis and a set of labeled bars horizontally or vertically. These bars represent the frequencies of variable values or the values themselves. Numbers on the y-axis of a vertical bar chart or the x-axis of a horizontal bar chart are called the scale.

Real-Life Application of Bar Charts

Let’s say a sales manager is presenting sales to their audience. Using a bar chart, he follows these steps.

Step 1: Selecting Data

The first step is to identify the specific data you will present to your audience.

The sales manager has highlighted these products for the presentation.

• Product A: Men’s Shoes
• Product B: Women’s Apparel
• Product C: Electronics
• Product D: Home Decor

Step 2: Choosing Orientation

Opt for a vertical layout for simplicity. Vertical bar charts help compare different categories in case there are not too many categories [1] . They can also help show different trends. A vertical bar chart is used where each bar represents one of the four chosen products. After plotting the data, it is seen that the height of each bar directly represents the sales performance of the respective product.

It is visible that the tallest bar (Electronics – Product C) is showing the highest sales. However, the shorter bars (Women’s Apparel – Product B and Home Decor – Product D) need attention. It indicates areas that require further analysis or strategies for improvement.

Step 3: Colorful Insights

Different colors are used to differentiate each product. It is essential to show a color-coded chart where the audience can distinguish between products.

• Men’s Shoes (Product A): Yellow
• Women’s Apparel (Product B): Orange
• Electronics (Product C): Violet
• Home Decor (Product D): Blue

Bar charts are straightforward and easily understandable for presenting data. They are versatile when comparing products or any categorical data [2] . Bar charts adapt seamlessly to retail scenarios. Despite that, bar charts have a few shortcomings. They cannot illustrate data trends over time. Besides, overloading the chart with numerous products can lead to visual clutter, diminishing its effectiveness.

For more information, check our collection of bar chart templates for PowerPoint .

Line graphs help illustrate data trends, progressions, or fluctuations by connecting a series of data points called ‘markers’ with straight line segments. This provides a straightforward representation of how values change [5] . Their versatility makes them invaluable for scenarios requiring a visual understanding of continuous data. In addition, line graphs are also useful for comparing multiple datasets over the same timeline. Using multiple line graphs allows us to compare more than one data set. They simplify complex information so the audience can quickly grasp the ups and downs of values. From tracking stock prices to analyzing experimental results, you can use line graphs to show how data changes over a continuous timeline. They show trends with simplicity and clarity.

Real-life Application of Line Graphs

To understand line graphs thoroughly, we will use a real case. Imagine you’re a financial analyst presenting a tech company’s monthly sales for a licensed product over the past year. Investors want insights into sales behavior by month, how market trends may have influenced sales performance and reception to the new pricing strategy. To present data via a line graph, you will complete these steps.

First, you need to gather the data. In this case, your data will be the sales numbers. For example:

• January: $45,000
• February: $55,000
• March: $45,000
• April: $60,000
• May: $ 70,000
• June: $65,000
• July: $62,000
• August: $68,000
• September: $81,000
• October: $76,000
• November: $87,000
• December: $91,000

After choosing the data, the next step is to select the orientation. Like bar charts, you can use vertical or horizontal line graphs. However, we want to keep this simple, so we will keep the timeline (x-axis) horizontal while the sales numbers (y-axis) vertical.

Step 3: Connecting Trends

After adding the data to your preferred software, you will plot a line graph. In the graph, each month’s sales are represented by data points connected by a line.

Step 4: Adding Clarity with Color

If there are multiple lines, you can also add colors to highlight each one, making it easier to follow.

Line graphs excel at visually presenting trends over time. These presentation aids identify patterns, like upward or downward trends. However, too many data points can clutter the graph, making it harder to interpret. Line graphs work best with continuous data but are not suitable for categories.

For more information, check our collection of line chart templates for PowerPoint and our article about how to make a presentation graph .

A data dashboard is a visual tool for analyzing information. Different graphs, charts, and tables are consolidated in a layout to showcase the information required to achieve one or more objectives. Dashboards help quickly see Key Performance Indicators (KPIs). You don’t make new visuals in the dashboard; instead, you use it to display visuals you’ve already made in worksheets [3] .

Keeping the number of visuals on a dashboard to three or four is recommended. Adding too many can make it hard to see the main points [4]. Dashboards can be used for business analytics to analyze sales, revenue, and marketing metrics at a time. They are also used in the manufacturing industry, as they allow users to grasp the entire production scenario at the moment while tracking the core KPIs for each line.

Real-Life Application of a Dashboard

Consider a project manager presenting a software development project’s progress to a tech company’s leadership team. He follows the following steps.

Step 1: Defining Key Metrics

To effectively communicate the project’s status, identify key metrics such as completion status, budget, and bug resolution rates. Then, choose measurable metrics aligned with project objectives.

Step 2: Choosing Visualization Widgets

After finalizing the data, presentation aids that align with each metric are selected. For this project, the project manager chooses a progress bar for the completion status and uses bar charts for budget allocation. Likewise, he implements line charts for bug resolution rates.

Step 3: Dashboard Layout

Key metrics are prominently placed in the dashboard for easy visibility, and the manager ensures that it appears clean and organized.

Dashboards provide a comprehensive view of key project metrics. Users can interact with data, customize views, and drill down for detailed analysis. However, creating an effective dashboard requires careful planning to avoid clutter. Besides, dashboards rely on the availability and accuracy of underlying data sources.

For more information, check our article on how to design a dashboard presentation , and discover our collection of dashboard PowerPoint templates .

Treemap charts represent hierarchical data structured in a series of nested rectangles [6] . As each branch of the ‘tree’ is given a rectangle, smaller tiles can be seen representing sub-branches, meaning elements on a lower hierarchical level than the parent rectangle. Each one of those rectangular nodes is built by representing an area proportional to the specified data dimension.

Treemaps are useful for visualizing large datasets in compact space. It is easy to identify patterns, such as which categories are dominant. Common applications of the treemap chart are seen in the IT industry, such as resource allocation, disk space management, website analytics, etc. Also, they can be used in multiple industries like healthcare data analysis, market share across different product categories, or even in finance to visualize portfolios.

Real-Life Application of a Treemap Chart

Let’s consider a financial scenario where a financial team wants to represent the budget allocation of a company. There is a hierarchy in the process, so it is helpful to use a treemap chart. In the chart, the top-level rectangle could represent the total budget, and it would be subdivided into smaller rectangles, each denoting a specific department. Further subdivisions within these smaller rectangles might represent individual projects or cost categories.

Step 1: Define Your Data Hierarchy

While presenting data on the budget allocation, start by outlining the hierarchical structure. The sequence will be like the overall budget at the top, followed by departments, projects within each department, and finally, individual cost categories for each project.

• Top-level rectangle: Total Budget
• Second-level rectangles: Departments (Engineering, Marketing, Sales)
• Third-level rectangles: Projects within each department
• Fourth-level rectangles: Cost categories for each project (Personnel, Marketing Expenses, Equipment)

Step 2: Choose a Suitable Tool

It’s time to select a data visualization tool supporting Treemaps. Popular choices include Tableau, Microsoft Power BI, PowerPoint, or even coding with libraries like D3.js. It is vital to ensure that the chosen tool provides customization options for colors, labels, and hierarchical structures.

Here, the team uses PowerPoint for this guide because of its user-friendly interface and robust Treemap capabilities.

Step 3: Make a Treemap Chart with PowerPoint

After opening the PowerPoint presentation, they chose “SmartArt” to form the chart. The SmartArt Graphic window has a “Hierarchy” category on the left.  Here, you will see multiple options. You can choose any layout that resembles a Treemap. The “Table Hierarchy” or “Organization Chart” options can be adapted. The team selects the Table Hierarchy as it looks close to a Treemap.

Step 5: Input Your Data

After that, a new window will open with a basic structure. They add the data one by one by clicking on the text boxes. They start with the top-level rectangle, representing the total budget.  

Step 6: Customize the Treemap

By clicking on each shape, they customize its color, size, and label. At the same time, they can adjust the font size, style, and color of labels by using the options in the “Format” tab in PowerPoint. Using different colors for each level enhances the visual difference.

Treemaps excel at illustrating hierarchical structures. These charts make it easy to understand relationships and dependencies. They efficiently use space, compactly displaying a large amount of data, reducing the need for excessive scrolling or navigation. Additionally, using colors enhances the understanding of data by representing different variables or categories.

In some cases, treemaps might become complex, especially with deep hierarchies.  It becomes challenging for some users to interpret the chart. At the same time, displaying detailed information within each rectangle might be constrained by space. It potentially limits the amount of data that can be shown clearly. Without proper labeling and color coding, there’s a risk of misinterpretation.

A heatmap is a data visualization tool that uses color coding to represent values across a two-dimensional surface. In these, colors replace numbers to indicate the magnitude of each cell. This color-shaded matrix display is valuable for summarizing and understanding data sets with a glance [7] . The intensity of the color corresponds to the value it represents, making it easy to identify patterns, trends, and variations in the data.

As a tool, heatmaps help businesses analyze website interactions, revealing user behavior patterns and preferences to enhance overall user experience. In addition, companies use heatmaps to assess content engagement, identifying popular sections and areas of improvement for more effective communication. They excel at highlighting patterns and trends in large datasets, making it easy to identify areas of interest.

We can implement heatmaps to express multiple data types, such as numerical values, percentages, or even categorical data. Heatmaps help us easily spot areas with lots of activity, making them helpful in figuring out clusters [8] . When making these maps, it is important to pick colors carefully. The colors need to show the differences between groups or levels of something. And it is good to use colors that people with colorblindness can easily see.

Check our detailed guide on how to create a heatmap here. Also discover our collection of heatmap PowerPoint templates .

Pie charts are circular statistical graphics divided into slices to illustrate numerical proportions. Each slice represents a proportionate part of the whole, making it easy to visualize the contribution of each component to the total.

The size of the pie charts is influenced by the value of data points within each pie. The total of all data points in a pie determines its size. The pie with the highest data points appears as the largest, whereas the others are proportionally smaller. However, you can present all pies of the same size if proportional representation is not required [9] . Sometimes, pie charts are difficult to read, or additional information is required. A variation of this tool can be used instead, known as the donut chart , which has the same structure but a blank center, creating a ring shape. Presenters can add extra information, and the ring shape helps to declutter the graph.

Pie charts are used in business to show percentage distribution, compare relative sizes of categories, or present straightforward data sets where visualizing ratios is essential.

Real-Life Application of Pie Charts

Consider a scenario where you want to represent the distribution of the data. Each slice of the pie chart would represent a different category, and the size of each slice would indicate the percentage of the total portion allocated to that category.

Step 1: Define Your Data Structure

Imagine you are presenting the distribution of a project budget among different expense categories.

• Column A: Expense Categories (Personnel, Equipment, Marketing, Miscellaneous)
• Column B: Budget Amounts ($40,000, $30,000, $20,000, $10,000) Column B represents the values of your categories in Column A.

Step 2: Insert a Pie Chart

Using any of the accessible tools, you can create a pie chart. The most convenient tools for forming a pie chart in a presentation are presentation tools such as PowerPoint or Google Slides.  You will notice that the pie chart assigns each expense category a percentage of the total budget by dividing it by the total budget.

For instance:

• Personnel: $40,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 40%
• Equipment: $30,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 30%
• Marketing: $20,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 20%
• Miscellaneous: $10,000 / ($40,000 + $30,000 + $20,000 + $10,000) = 10%

You can make a chart out of this or just pull out the pie chart from the data.

3D pie charts and 3D donut charts are quite popular among the audience. They stand out as visual elements in any presentation slide, so let’s take a look at how our pie chart example would look in 3D pie chart format.

Step 03: Results Interpretation

The pie chart visually illustrates the distribution of the project budget among different expense categories. Personnel constitutes the largest portion at 40%, followed by equipment at 30%, marketing at 20%, and miscellaneous at 10%. This breakdown provides a clear overview of where the project funds are allocated, which helps in informed decision-making and resource management. It is evident that personnel are a significant investment, emphasizing their importance in the overall project budget.

Pie charts provide a straightforward way to represent proportions and percentages. They are easy to understand, even for individuals with limited data analysis experience. These charts work well for small datasets with a limited number of categories.

However, a pie chart can become cluttered and less effective in situations with many categories. Accurate interpretation may be challenging, especially when dealing with slight differences in slice sizes. In addition, these charts are static and do not effectively convey trends over time.

For more information, check our collection of pie chart templates for PowerPoint .

Histograms present the distribution of numerical variables. Unlike a bar chart that records each unique response separately, histograms organize numeric responses into bins and show the frequency of reactions within each bin [10] . The x-axis of a histogram shows the range of values for a numeric variable. At the same time, the y-axis indicates the relative frequencies (percentage of the total counts) for that range of values.

Whenever you want to understand the distribution of your data, check which values are more common, or identify outliers, histograms are your go-to. Think of them as a spotlight on the story your data is telling. A histogram can provide a quick and insightful overview if you’re curious about exam scores, sales figures, or any numerical data distribution.

Real-Life Application of a Histogram

In the histogram data analysis presentation example, imagine an instructor analyzing a class’s grades to identify the most common score range. A histogram could effectively display the distribution. It will show whether most students scored in the average range or if there are significant outliers.

Step 1: Gather Data

He begins by gathering the data. The scores of each student in class are gathered to analyze exam scores.

After arranging the scores in ascending order, bin ranges are set.

Step 2: Define Bins

Bins are like categories that group similar values. Think of them as buckets that organize your data. The presenter decides how wide each bin should be based on the range of the values. For instance, the instructor sets the bin ranges based on score intervals: 60-69, 70-79, 80-89, and 90-100.

Step 3: Count Frequency

Now, he counts how many data points fall into each bin. This step is crucial because it tells you how often specific ranges of values occur. The result is the frequency distribution, showing the occurrences of each group.

Here, the instructor counts the number of students in each category.

• 60-69: 1 student (Kate)
• 70-79: 4 students (David, Emma, Grace, Jack)
• 80-89: 7 students (Alice, Bob, Frank, Isabel, Liam, Mia, Noah)
• 90-100: 3 students (Clara, Henry, Olivia)

Step 4: Create the Histogram

It’s time to turn the data into a visual representation. Draw a bar for each bin on a graph. The width of the bar should correspond to the range of the bin, and the height should correspond to the frequency.  To make your histogram understandable, label the X and Y axes.

In this case, the X-axis should represent the bins (e.g., test score ranges), and the Y-axis represents the frequency.

The histogram of the class grades reveals insightful patterns in the distribution. Most students, with seven students, fall within the 80-89 score range. The histogram provides a clear visualization of the class’s performance. It showcases a concentration of grades in the upper-middle range with few outliers at both ends. This analysis helps in understanding the overall academic standing of the class. It also identifies the areas for potential improvement or recognition.

Thus, histograms provide a clear visual representation of data distribution. They are easy to interpret, even for those without a statistical background. They apply to various types of data, including continuous and discrete variables. One weak point is that histograms do not capture detailed patterns in students’ data, with seven compared to other visualization methods.

A scatter plot is a graphical representation of the relationship between two variables. It consists of individual data points on a two-dimensional plane. This plane plots one variable on the x-axis and the other on the y-axis. Each point represents a unique observation. It visualizes patterns, trends, or correlations between the two variables.

Scatter plots are also effective in revealing the strength and direction of relationships. They identify outliers and assess the overall distribution of data points. The points’ dispersion and clustering reflect the relationship’s nature, whether it is positive, negative, or lacks a discernible pattern. In business, scatter plots assess relationships between variables such as marketing cost and sales revenue. They help present data correlations and decision-making.

Real-Life Application of Scatter Plot

A group of scientists is conducting a study on the relationship between daily hours of screen time and sleep quality. After reviewing the data, they managed to create this table to help them build a scatter plot graph:

In the provided example, the x-axis represents Daily Hours of Screen Time, and the y-axis represents the Sleep Quality Rating.

The scientists observe a negative correlation between the amount of screen time and the quality of sleep. This is consistent with their hypothesis that blue light, especially before bedtime, has a significant impact on sleep quality and metabolic processes.

There are a few things to remember when using a scatter plot. Even when a scatter diagram indicates a relationship, it doesn’t mean one variable affects the other. A third factor can influence both variables. The more the plot resembles a straight line, the stronger the relationship is perceived [11] . If it suggests no ties, the observed pattern might be due to random fluctuations in data. When the scatter diagram depicts no correlation, whether the data might be stratified is worth considering.

Choosing the appropriate data presentation type is crucial when making a presentation . Understanding the nature of your data and the message you intend to convey will guide this selection process. For instance, when showcasing quantitative relationships, scatter plots become instrumental in revealing correlations between variables. If the focus is on emphasizing parts of a whole, pie charts offer a concise display of proportions. Histograms, on the other hand, prove valuable for illustrating distributions and frequency patterns. 

Bar charts provide a clear visual comparison of different categories. Likewise, line charts excel in showcasing trends over time, while tables are ideal for detailed data examination. Starting a presentation on data presentation types involves evaluating the specific information you want to communicate and selecting the format that aligns with your message. This ensures clarity and resonance with your audience from the beginning of your presentation.

1. Fact Sheet Dashboard for Data Presentation

Convey all the data you need to present in this one-pager format, an ideal solution tailored for users looking for presentation aids. Global maps, donut chats, column graphs, and text neatly arranged in a clean layout presented in light and dark themes.

Use This Template

2. 3D Column Chart Infographic PPT Template

Represent column charts in a highly visual 3D format with this PPT template. A creative way to present data, this template is entirely editable, and we can craft either a one-page infographic or a series of slides explaining what we intend to disclose point by point.

3. Data Circles Infographic PowerPoint Template

An alternative to the pie chart and donut chart diagrams, this template features a series of curved shapes with bubble callouts as ways of presenting data. Expand the information for each arch in the text placeholder areas.

4. Colorful Metrics Dashboard for Data Presentation

This versatile dashboard template helps us in the presentation of the data by offering several graphs and methods to convert numbers into graphics. Implement it for e-commerce projects, financial projections, project development, and more.

5. Animated Data Presentation Tools for PowerPoint & Google Slides

A slide deck filled with most of the tools mentioned in this article, from bar charts, column charts, treemap graphs, pie charts, histogram, etc. Animated effects make each slide look dynamic when sharing data with stakeholders.

6. Statistics Waffle Charts PPT Template for Data Presentations

This PPT template helps us how to present data beyond the typical pie chart representation. It is widely used for demographics, so it’s a great fit for marketing teams, data science professionals, HR personnel, and more.

7. Data Presentation Dashboard Template for Google Slides

A compendium of tools in dashboard format featuring line graphs, bar charts, column charts, and neatly arranged placeholder text areas. 

8. Weather Dashboard for Data Presentation

Share weather data for agricultural presentation topics, environmental studies, or any kind of presentation that requires a highly visual layout for weather forecasting on a single day. Two color themes are available.

9. Social Media Marketing Dashboard Data Presentation Template

Intended for marketing professionals, this dashboard template for data presentation is a tool for presenting data analytics from social media channels. Two slide layouts featuring line graphs and column charts.

10. Project Management Summary Dashboard Template

A tool crafted for project managers to deliver highly visual reports on a project’s completion, the profits it delivered for the company, and expenses/time required to execute it. 4 different color layouts are available.

11. Profit & Loss Dashboard for PowerPoint and Google Slides

A must-have for finance professionals. This typical profit & loss dashboard includes progress bars, donut charts, column charts, line graphs, and everything that’s required to deliver a comprehensive report about a company’s financial situation.

Overwhelming visuals

One of the mistakes related to using data-presenting methods is including too much data or using overly complex visualizations. They can confuse the audience and dilute the key message.

Inappropriate chart types

Choosing the wrong type of chart for the data at hand can lead to misinterpretation. For example, using a pie chart for data that doesn’t represent parts of a whole is not right.

Lack of context

Failing to provide context or sufficient labeling can make it challenging for the audience to understand the significance of the presented data.

Inconsistency in design

Using inconsistent design elements and color schemes across different visualizations can create confusion and visual disarray.

Failure to provide details

Simply presenting raw data without offering clear insights or takeaways can leave the audience without a meaningful conclusion.

Lack of focus

Not having a clear focus on the key message or main takeaway can result in a presentation that lacks a central theme.

Visual accessibility issues

Overlooking the visual accessibility of charts and graphs can exclude certain audience members who may have difficulty interpreting visual information.

In order to avoid these mistakes in data presentation, presenters can benefit from using presentation templates . These templates provide a structured framework. They ensure consistency, clarity, and an aesthetically pleasing design, enhancing data communication’s overall impact.

Understanding and choosing data presentation types are pivotal in effective communication. Each method serves a unique purpose, so selecting the appropriate one depends on the nature of the data and the message to be conveyed. The diverse array of presentation types offers versatility in visually representing information, from bar charts showing values to pie charts illustrating proportions. 

Using the proper method enhances clarity, engages the audience, and ensures that data sets are not just presented but comprehensively understood. By appreciating the strengths and limitations of different presentation types, communicators can tailor their approach to convey information accurately, developing a deeper connection between data and audience understanding.

[1] Government of Canada, S.C. (2021) 5 Data Visualization 5.2 Bar Chart , 5.2 Bar chart .  https://www150.statcan.gc.ca/n1/edu/power-pouvoir/ch9/bargraph-diagrammeabarres/5214818-eng.htm

[2] Kosslyn, S.M., 1989. Understanding charts and graphs. Applied cognitive psychology, 3(3), pp.185-225. https://apps.dtic.mil/sti/pdfs/ADA183409.pdf

[3] Creating a Dashboard . https://it.tufts.edu/book/export/html/1870

[4] https://www.goldenwestcollege.edu/research/data-and-more/data-dashboards/index.html

[5] https://www.mit.edu/course/21/21.guide/grf-line.htm

[6] Jadeja, M. and Shah, K., 2015, January. Tree-Map: A Visualization Tool for Large Data. In GSB@ SIGIR (pp. 9-13). https://ceur-ws.org/Vol-1393/gsb15proceedings.pdf#page=15

[7] Heat Maps and Quilt Plots. https://www.publichealth.columbia.edu/research/population-health-methods/heat-maps-and-quilt-plots

[8] EIU QGIS WORKSHOP. https://www.eiu.edu/qgisworkshop/heatmaps.php

[9] About Pie Charts.  https://www.mit.edu/~mbarker/formula1/f1help/11-ch-c8.htm

[10] Histograms. https://sites.utexas.edu/sos/guided/descriptive/numericaldd/descriptiven2/histogram/ [11] https://asq.org/quality-resources/scatter-diagram

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What is Data Visualization? Definition, Examples, Best Practices

This guide provides an introduction to data visualization, including real-world examples, best practices and editable templates.

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Resource Details

June 5, 2020

Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart, infographic, diagram, or map.

The field of data visualization combines both art and data science. While data visualization can be creative and pleasing to look at, it should also be functional in its visual communication of the data.

This resource explains the fundamentals of data visualization, including examples of different types of data visualizations and when and how to use them to illustrate findings and insights.

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A data presentation is a slide deck that shares quantitative information with an audience using visuals and effective presentation techniques . The goal is to make complex data easily understandable and actionable using data presentation examples like graphs and charts, tables, dashboards, and clear text explanations. 

Data presentations help highlight trends, patterns, and insights, allowing the audience to grasp complicated concepts or trends quickly. This makes it easier for them to make informed decisions or conduct deeper analysis.

Data visualization in presentations is used in every field, from academia to business and industry. Raw data is often too complex to understand directly, so data analysis breaks it down into charts and graphs. These tools help turn raw data into useful information.

Once the information is extracted, it’s presented graphically. A good presentation can significantly enhance understanding and response.

Think of data presentation as storytelling in business presentations with charts. A common mistake is assuming the audience understands the data as well as the presenter. Always consider your audience’s knowledge level and what information they need when you present your data.

To present the data effectively:

1. Provide context to help the audience understand the numbers.

2. Compare data groups using visual aids.

3. Step back and view the data from the audience’s perspective.

Data presentations are crucial in nearly every industry, helping professionals share their findings clearly after analyzing data.

Key Takeaways

• Simplifying Complex Data: Data presentations turn complex data into easy-to-understand visuals and narratives, helping audiences quickly grasp trends and insights for informed decision-making.
• Versatile Tools: Various tools like bar charts, dashboards, pie charts, histograms, scatter plots, pictograms, textual presentations, and tables each serve unique purposes, enhancing the clarity and impact of the data.
• Audience Consideration: Tailor your presentation to the audience’s knowledge level, providing context and using simple visuals to make the information accessible and actionable.
• Effective Data Storytelling: Combining clear context, organized visuals, and thoughtful presentation ensures that the data’s story is conveyed effectively, supporting better business decisions and success.

Following are 9 data presentation tools for business success.

Bar charts are a simple yet powerful method of presentation of the data using rectangular bars to show quantities or frequencies. They make it easy to spot patterns or trends at a glance. Bar charts can be vertical (column charts) or horizontal, depending on how you want to display your data.

In a bar graph, categories are displayed on one axis, usually the x-axis for vertical charts and the y-axis for horizontal ones. The bars’ lengths represent the values or frequencies of these categories, with the scale marked on the opposite axis.

These charts are ideal for comparing data across different categories or showing trends over time. Each bar’s height (or length in a horizontal chart) is directly proportional to the value it represents. This visual representation helps illustrate differences or changes in data.

Bar charts are versatile tools in business reports, academic presentations, and more. To make your bar charts effective:

• Ensure they are concise and have easy-to-read labels.
• Avoid clutter by not including too many categories, making the chart hard to read.
• Keep it simple to maintain clarity and impact, whether your bars go up or sideways.

Line Graphs

Line graphs show how data changes over time or with continuous variables. They connect points of data with straight lines, making it easy to see trends and fluctuations. These graphs are handy when comparing multiple datasets over the same timeline.

Using line graphs, you can track things like stock prices, sales projections, or experimental results. The x-axis represents time or another continuous variable, while the y-axis shows the data values. This setup allows you to understand the ups and downs in the data quickly.

To make your graphs effective, keep them simple. Avoid overcrowding with too many lines, highlight significant changes, use labels, and give your graph a clear, catchy title. This will help your audience grasp the information quickly and easily.

A data dashboard is a data analysis presentation example for analyzing information. It combines different graphs, charts, and tables in one layout to show the information needed to meet one or more objectives. Dashboards help quickly see Key Performance Indicators (KPIs) by displaying visuals you’ve already made in worksheets.

It’s best to keep the number of visuals on a dashboard to three or four. Adding too many can make it hard to see the main points. Dashboards are helpful for business analytics, like analyzing sales, revenue, and marketing metrics. In manufacturing, they help users understand the production scenario and track critical KPIs for each production line.

Dashboards represent vital points of data or metrics in an easy-to-understand way. They are often an  interactive presentation idea , allowing users to drill down into the data or view different aspects of it.

Pie charts are circular graphs divided into parts to show numerical proportions. Each portion represents a part of the whole, making it easy to see each component’s contribution to the total.

The size of each slice is determined by its value relative to the total. A pie chart with more significant points of data will have larger slices, and the whole chart will be more important. However, you can make all pies the same size if proportional representation isn’t necessary.

Pie charts are helpful in business to show percentage distributions, compare category sizes, or present simple data sets where visualizing ratios is essential. They work best with fewer variables. For more variables, it’s better to use a pie chart calculator that helps to create pie charts easily for various data sets with different color slices. 

Each “slice” represents a fraction of the total, and the size of each slice shows its share of the whole. Pie charts are excellent for showing how a whole is divided into parts, such as survey results or demographic data.

While pie charts are great for simple distributions, they can get confusing with too many categories or slight differences in proportions. To keep things clear, label each slice with percentages or values and use a legend if there are many categories. If more detail is needed, consider using a donut chart with a blank center for extra information and a less cluttered look.

A histogram is a graphical presentation of data  to help in understanding the distribution of numerical values. Unlike bar charts that show each response separately, histograms group numeric responses into bins and display the frequency of reactions within each bin. The x-axis denotes the range of values, while the y-axis shows the frequency of those values.

Histograms are useful for understanding your data’s distribution, identifying shared values, and spotting outliers. They highlight the story your data tells, whether it’s exam scores, sales figures, or any other numerical data.

Histograms are great for visualizing the distribution and frequency of a single variable. They divide the data into bins, and the height of each bar indicates how many points of data fall into that bin. This makes it easy to see trends like peaks, gaps, or skewness in your data.

To make your histogram effective, choose bin sizes that capture meaningful patterns. Clear axis labels and titles also help in explaining the data distribution.

Scatter Plot

Using individual data points, a scatter plot chart is a presentation of data in visual form to show the relationship between two variables. Each variable is plotted along the x-axis and y-axis, respectively. Each point on the scatter plot represents a single observation.

Scatter plots help visualize patterns, trends, and correlations between the two variables. They can also help identify outliers and understand the overall distribution of data points. The way the points are spread out or clustered together can indicate whether there is a positive, negative, or no clear relationship between the variables.

Scatter plots can be used in practical applications, such as in business, to show how variables like marketing cost and sales revenue are related. They help understand data correlations, which aids in decision-making.

To make scatter plots more effective, consider adding trendlines or regression analysis to highlight patterns. Labeling key data points or tooltips can provide additional information and make the chart easier to interpret.

A pictogram is the simplest form of data presentation and analysis, often used in schools and universities to help students grasp concepts more effectively through pictures.

This type of diagram uses images to represent data. For example, you could draw five books to show the number of books sold in the first week of release, with each image representing 1,000 books. If consumers bought 5,000 books, you would display five book images.

Using simple icons or images makes the information visually intuitive. Instead of relying on numbers or complex graphs, pictograms use straightforward symbols to depict data points. For example, a thumbs-up emoji can illustrate customer satisfaction levels, with each emoji representing a different level of satisfaction.

Pictograms are excellent for visual data presentation. Choose symbols that are easy to interpret and relevant to the data to ensure clarity. Consistent scaling and a legend explaining the symbols’ meanings are essential for an effective presentation.

Textual Presentation

Textual presentation uses words to describe the relationships between pieces of information. This method helps share details that can’t be shown in a graph or table. For example, researchers often present findings in a study textually to provide extra context or explanation. A textual presentation can make the information more transparent.

This type of presentation is common in research and for introducing new ideas. Unlike charts or graphs, it relies solely on paragraphs and words.

Textual presentation also involves using written content, such as annotations or explanatory text, to explain or complement data. While it doesn’t use visual presentation aids like charts, it is a widely used method for presenting qualitative data. Think of it as the narrative that guides your audience through the data.

Adequate textual data may make complex information more accessible. Breaking down complex details into bullet points or short paragraphs helps your audience understand the significance of numbers and visuals. Headings can guide the reader’s attention and tell a coherent story.

Tabular Presentation

Tabular presentation uses tables to share information by organizing data in rows and columns. This method is useful for comparing data and visualizing information. Researchers often use tables to analyze data in various classifications:

Qualitative classification: This includes qualities like nationality, age, social status, appearance, and personality traits, helping to compare sociological and psychological information.

Quantitative classification: This covers items you can count or number.

Spatial classification: This deals with data based on location, such as information about a city, state, or region.

Temporal classification: This involves time-based data measured in seconds, hours, days, or weeks.

Tables simplify data, making it easily consumable, allow for side-by-side comparisons, and save space in your presentation by condensing information.

Using rows and columns, tabular presentation focuses on clarity and precision. It’s about displaying numerical data in a structured grid, clearly showing individual data points. Tables are invaluable for showcasing detailed data, facilitating comparisons, and presenting exact numerical information. They are commonly used in reports, spreadsheets, and academic papers.

Organize tables neatly with clear headers and appropriate column widths to ensure readability. Highlight important data points or patterns using shading or font formatting. Tables are simple and effective, especially when the audience needs to know precise figures.

Elevate Business Decisions with Effective Data Presentations

Data presentations are essential for transforming complex data into understandable and actionable insights. Data presentations simplify the process of interpreting quantitative information by utilizing data presentation examples like charts, graphs, tables, infographics, dashboards, and clear narratives. This method of storytelling with visuals highlights trends, patterns, and insights, enabling audiences to make informed decisions quickly.

In business, data analysis presentations are invaluable. Different types of presentation tools like bar charts help compare categories and track changes over time, while dashboards consolidate various metrics into a comprehensive view. Pie charts and histograms offer clear views of distributions and proportions, aiding in grasping the bigger picture. Scatter plots reveal relationships between variables, and pictograms make data visually intuitive. Textual presentations and tables provide detailed context and precise figures, which are essential for thorough analysis and comparison.

Consider the audience’s knowledge level to tailor the best way to present data in PowerPoint. Clear context, simple visuals, and thoughtful organization ensure the data’s story is easily understood and impactful. Mastering these nine data presentation types can significantly enhance business success by making data-driven decisions more accessible and practical.

Frequently Asked Questions (FAQs)

1. What is a data presentation?

A data presentation is a slide deck that uses visuals and narrative techniques to make complex data easy to understand and actionable. It includes charts, graphs, tables, infographics, dashboards, and clear text explanations.

2. Why are data presentations important in business?

Data presentations are crucial because they help highlight trends, patterns, and insights, making it easier for the audience to understand complicated concepts. This enables better decision-making and deeper analysis.

3. What types of data presentation tools are commonly used?

Common tools include bar charts, line graphs, dashboards, pie charts, histograms, scatter plots, pictograms, textual presentations, and tables. Each tool has a unique way of representing data to aid understanding.

4. How can I ensure my data presentation is effective?

To ensure effectiveness, provide context, compare data sets using visual aids, consider your audience’s knowledge level, and keep visuals simple. Organizing information thoughtfully and avoiding clutter enhances clarity and impact.

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Prezentium’s services are designed to help you make the most of your data, from bar charts to dashboards, ensuring your presentations are informative and visually engaging. Let us help you tell your data’s story in a way that resonates. Contact Prezentium today to elevate your business presentations.

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10 Methods of Data Presentation That Really Work in 2024

Leah Nguyen • 15 July, 2024 • 13 min read

Have you ever presented a data report to your boss/coworkers/teachers thinking it was super dope like you’re some cyber hacker living in the Matrix, but all they saw was a pile of static numbers that seemed pointless and didn't make sense to them?

Understanding digits is rigid . Making people from non-analytical backgrounds understand those digits is even more challenging.

How can you clear up those confusing numbers and make your presentation as clear as the day? Let's check out these best ways to present data. 💎

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Data Presentation - What Is It?

The term ’data presentation’ relates to the way you present data in a way that makes even the most clueless person in the room understand. 

Some say it’s witchcraft (you’re manipulating the numbers in some ways), but we’ll just say it’s the power of turning dry, hard numbers or digits into a visual showcase that is easy for people to digest.

Presenting data correctly can help your audience understand complicated processes, identify trends, and instantly pinpoint whatever is going on without exhausting their brains.

Good data presentation helps…

• Make informed decisions and arrive at positive outcomes . If you see the sales of your product steadily increase throughout the years, it’s best to keep milking it or start turning it into a bunch of spin-offs (shoutout to Star Wars👀).
• Reduce the time spent processing data . Humans can digest information graphically 60,000 times faster than in the form of text. Grant them the power of skimming through a decade of data in minutes with some extra spicy graphs and charts.
• Communicate the results clearly . Data does not lie. They’re based on factual evidence and therefore if anyone keeps whining that you might be wrong, slap them with some hard data to keep their mouths shut.
• Add to or expand the current research . You can see what areas need improvement, as well as what details often go unnoticed while surfing through those little lines, dots or icons that appear on the data board.

Methods of Data Presentation and Examples

Imagine you have a delicious pepperoni, extra-cheese pizza. You can decide to cut it into the classic 8 triangle slices, the party style 12 square slices, or get creative and abstract on those slices. 

There are various ways to cut a pizza and you get the same variety with how you present your data. In this section, we will bring you the 10 ways to slice a pizza - we mean to present your data - that will make your company’s most important asset as clear as day. Let's dive into 10 ways to present data efficiently.

#1 - Tabular 

Among various types of data presentation, tabular is the most fundamental method, with data presented in rows and columns. Excel or Google Sheets would qualify for the job. Nothing fancy.

This is an example of a tabular presentation of data on Google Sheets. Each row and column has an attribute (year, region, revenue, etc.), and you can do a custom format to see the change in revenue throughout the year.

When presenting data as text, all you do is write your findings down in paragraphs and bullet points, and that’s it. A piece of cake to you, a tough nut to crack for whoever has to go through all of the reading to get to the point.

• 65% of email users worldwide access their email via a mobile device.
• Emails that are optimised for mobile generate 15% higher click-through rates.
• 56% of brands using emojis in their email subject lines had a higher open rate.

(Source: CustomerThermometer )

All the above quotes present statistical information in textual form. Since not many people like going through a wall of texts, you’ll have to figure out another route when deciding to use this method, such as breaking the data down into short, clear statements, or even as catchy puns if you’ve got the time to think of them.

#3 - Pie chart

A pie chart (or a ‘donut chart’ if you stick a hole in the middle of it) is a circle divided into slices that show the relative sizes of data within a whole. If you’re using it to show percentages, make sure all the slices add up to 100%.

The pie chart is a familiar face at every party and is usually recognised by most people. However, one setback of using this method is our eyes sometimes can’t identify the differences in slices of a circle, and it’s nearly impossible to compare similar slices from two different pie charts, making them the villains in the eyes of data analysts.

#4 - Bar chart

The bar chart is a chart that presents a bunch of items from the same category, usually in the form of rectangular bars that are placed at an equal distance from each other. Their heights or lengths depict the values they represent.

They can be as simple as this:

Or more complex and detailed like this example of data presentation. Contributing to an effective statistic presentation, this one is a grouped bar chart that not only allows you to compare categories but also the groups within them as well.

#5 - Histogram

Similar in appearance to the bar chart but the rectangular bars in histograms don’t often have the gap like their counterparts.

Instead of measuring categories like weather preferences or favourite films as a bar chart does, a histogram only measures things that can be put into numbers.

Teachers can use presentation graphs like a histogram to see which score group most of the students fall into, like in this example above.

#6 - Line graph

Recordings to ways of displaying data, we shouldn't overlook the effectiveness of line graphs. Line graphs are represented by a group of data points joined together by a straight line. There can be one or more lines to compare how several related things change over time. 

On a line chart’s horizontal axis, you usually have text labels, dates or years, while the vertical axis usually represents the quantity (e.g.: budget, temperature or percentage).

#7 - Pictogram graph

A pictogram graph uses pictures or icons relating to the main topic to visualise a small dataset. The fun combination of colours and illustrations makes it a frequent use at schools.

Pictograms are a breath of fresh air if you want to stay away from the monotonous line chart or bar chart for a while. However, they can present a very limited amount of data and sometimes they are only there for displays and do not represent real statistics.

#8 - Radar chart

If presenting five or more variables in the form of a bar chart is too stuffy then you should try using a radar chart, which is one of the most creative ways to present data.

Radar charts show data in terms of how they compare to each other starting from the same point. Some also call them ‘spider charts’ because each aspect combined looks like a spider web.

Radar charts can be a great use for parents who’d like to compare their child’s grades with their peers to lower their self-esteem. You can see that each angular represents a subject with a score value ranging from 0 to 100. Each student’s score across 5 subjects is highlighted in a different colour.

If you think that this method of data presentation somehow feels familiar, then you’ve probably encountered one while playing Pokémon .

#9 - Heat map

A heat map represents data density in colours. The bigger the number, the more colour intensity that data will be represented.

Most US citizens would be familiar with this data presentation method in geography. For elections, many news outlets assign a specific colour code to a state, with blue representing one candidate and red representing the other. The shade of either blue or red in each state shows the strength of the overall vote in that state.

Another great thing you can use a heat map for is to map what visitors to your site click on. The more a particular section is clicked the ‘hotter’ the colour will turn, from blue to bright yellow to red.

#10 - Scatter plot

If you present your data in dots instead of chunky bars, you’ll have a scatter plot. 

A scatter plot is a grid with several inputs showing the relationship between two variables. It’s good at collecting seemingly random data and revealing some telling trends.

For example, in this graph, each dot shows the average daily temperature versus the number of beach visitors across several days. You can see that the dots get higher as the temperature increases, so it’s likely that hotter weather leads to more visitors.

5 Data Presentation Mistakes to Avoid

#1 - assume your audience understands what the numbers represent.

You may know all the behind-the-scenes of your data since you’ve worked with them for weeks, but your audience doesn’t.

Showing without telling only invites more and more questions from your audience, as they have to constantly make sense of your data, wasting the time of both sides as a result.

While showing your data presentations, you should tell them what the data are about before hitting them with waves of numbers first. You can use interactive activities such as polls , word clouds , online quizzes and Q&A sections , combined with icebreaker games , to assess their understanding of the data and address any confusion beforehand.

#2 - Use the wrong type of chart

Charts such as pie charts must have a total of 100% so if your numbers accumulate to 193% like this example below, you’re definitely doing it wrong.

Before making a chart, ask yourself: what do I want to accomplish with my data? Do you want to see the relationship between the data sets, show the up and down trends of your data, or see how segments of one thing make up a whole?

Remember, clarity always comes first. Some data visualisations may look cool, but if they don’t fit your data, steer clear of them. 

#3 - Make it 3D

3D is a fascinating graphical presentation example. The third dimension is cool, but full of risks.

Can you see what’s behind those red bars? Because we can’t either. You may think that 3D charts add more depth to the design, but they can create false perceptions as our eyes see 3D objects closer and bigger than they appear, not to mention they cannot be seen from multiple angles.

#4 - Use different types of charts to compare contents in the same category

This is like comparing a fish to a monkey. Your audience won’t be able to identify the differences and make an appropriate correlation between the two data sets. 

Next time, stick to one type of data presentation only. Avoid the temptation of trying various data visualisation methods in one go and make your data as accessible as possible.

#5 - Bombard the audience with too much information

The goal of data presentation is to make complex topics much easier to understand, and if you’re bringing too much information to the table, you’re missing the point.

The more information you give, the more time it will take for your audience to process it all. If you want to make your data understandable and give your audience a chance to remember it, keep the information within it to an absolute minimum. You should end your session with open-ended questions to see what your participants really think.

What are the Best Methods of Data Presentation?

Finally, which is the best way to present data?

The answer is…

There is none! Each type of presentation has its own strengths and weaknesses and the one you choose greatly depends on what you’re trying to do. 

For example:

• Go for a scatter plot if you’re exploring the relationship between different data values, like seeing whether the sales of ice cream go up because of the temperature or because people are just getting more hungry and greedy each day?
• Go for a line graph if you want to mark a trend over time. 
• Go for a heat map if you like some fancy visualisation of the changes in a geographical location, or to see your visitors' behaviour on your website.
• Go for a pie chart (especially in 3D) if you want to be shunned by others because it was never a good idea👇

Frequently Asked Questions

What is a chart presentation.

A chart presentation is a way of presenting data or information using visual aids such as charts, graphs, and diagrams. The purpose of a chart presentation is to make complex information more accessible and understandable for the audience.

When can I use charts for the presentation?

Charts can be used to compare data, show trends over time, highlight patterns, and simplify complex information.

Why should you use charts for presentation?

You should use charts to ensure your contents and visuals look clean, as they are the visual representative, provide clarity, simplicity, comparison, contrast and super time-saving!

What are the 4 graphical methods of presenting data?

Histogram, Smoothed frequency graph, Pie diagram or Pie chart, Cumulative or ogive frequency graph, and Frequency Polygon.

Leah Nguyen

Words that convert, stories that stick. I turn complex ideas into engaging narratives - helping audiences learn, remember, and take action.

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More from AhaSlides

Mastering the Art of Presenting Data in PowerPoint

Presenting data in PowerPoint is easy. However, making it visually appealing and effective takes more time and effort. It’s not hard to bore your audience with the same old data presentation formats. So, there is one simple golden rule: Make it not boring.

When used correctly, data can add weight, authority, and punch to your message. It should support and highlight your ideas, making a concept come to life. But this begs the question: How to present data in PowerPoint?

After talking to our 200+ expert presentation designers, I compiled information about their best-kept secrets to presenting data in PowerPoint. 

Below, I’ll show our designers ' favorite ways to add data visualization for global customers and their expert tips for making your data shine. Read ahead and master the art of data visualization in PowerPoint!

Feel free to explore sections to find what's most useful!

How to present data in PowePoint: a step-by-step guide

Creative ways to present data in powerpoint.

• Tips for data visualization

Seeking to optimize your presentations? – 24Slides designers have got you covered!

How you present your data can make or break your presentation. It can make it stand out and stick with your audience, or make it fall flat from the go.

It’s not enough to just copy and paste your data into a presentation slide. Luckily, PowerPoint has many smart data visualization tools! You only need to put in your numbers, and PowerPoint will work it up for you.

Follow these steps, and I guarantee your presentations will level up!

1. Collect your data

First things first, and that is to have all your information ready. Especially for long business presentations, there can be a lot of information to consider when working on your slides. Having it all organized and ready to use will make the whole process much easier to go through.

Consider where your data comes from, whether from research, surveys, or databases. Make sure your data is accurate, up-to-date, and relevant to your presentation topic.

Your goal will be to create clear conclusions based on your data and highlight trends.

2. Know your audience

Knowing who your audience is and the one thing you want them to get from your data is vital. If you don’t have any idea where to start, you can begin with these key questions:

• What impact do you want your data to make on them?
• Is the subject of your presentation familiar to them?
• Are they fellow sales professionals?
• Are they interested in the relationships in the data you’re presenting?

By answering these, you'll be able to clearly understand the purpose of your data. As a storyteller, you want to capture your audience’s attention.

3. Choose a data visualization option

One key to data visualization in PowerPoint is being aware of your choices and picking the best one for your needs. This depends on the type of data you’re trying to showcase and your story.

When showcasing growth over time, you won’t use a spider chart but a line chart. If you show percentages, a circle graph will probably work better than a timeline. As you can see, knowing how to work with charts, graphs, and tables can level up your presentation.

Later, we’ll review some of the most common tools for data visualization in PowerPoint. This will include what these graphs and charts are best for and how to make the most of each. So read ahead for more information about how to present data in PowerPoint!

4. Be creative!

PowerPoint can assist with creating graphs and charts, but it's up to you to perfect them. Take into account that PowerPoint has many options. So, don't be afraid to think outside the box when presenting your data.

To enhance your presentation design, try out different color schemes, fonts, and layouts. Add images, icons, and visual elements to highlight your ideas.

If this sounds complicated to you, there's no need to worry. At the end of this article, you’ll find some easy tips for upgrading your data visualization design!

At this point, you might wonder: what is the best way to present data in PowerPoint? Well, let me tell you: it's all about charts. To accomplish a polished presentation, you must use charts instead of words. When visualizing quantitative data, a picture is worth a thousand words.

Based on +10 years of expertise, we've identified key chart types and creative ways to work with them. Let's delve into each one!

Line Charts

Line charts are a classic, which can make them boring. However, if done correctly, they can be striking and effective. But where does their popularity come from? Here's the answer: Line charts work great to show changes over time.

Another critical difference is that line charts are accumulative. For example, you can join them to a column chart to show different data at a glance. They allow data visualization effectively, making it easier to figure out.

To make the most of them, mastering how to work with line charts is essential. But there is good news: you will have a lot of freedom to customize them!

Download our Free Line Chart Template here .

Bar and column charts

Bar and column charts are another classic choice. Again, they are simple and great for comparing different categories. They organize them around two axes: one shows numbers, and the other shows what we want to compare.

But when should you use a bar chart or a column chart? A bar chart is better when comparing different categories and having long labels. A column chart, on the other hand, is better if you have a few categories and want to show changes over time.

You also have the waterfall option, which is perfect for highlighting the difference between gains and losses. It also adds a dynamic touch to your presentation!

Unsure how to implement these charts? Here's how to add a bar or a column chart in PowerPoint.

Download our Bar and Column Chart Template here .

Venn diagram

Venn diagrams are definitely something to consider when discussing data visualization—even if its focus is not quantitative data! Venn diagrams are best for showcasing similarities and differences between two (or more) categories or products. 

By using overlapping circles, you can quickly and easily see common features between separate ideas. The shared space of the circles shows what is the same between the groups. However, items in the outer parts of each circle show what isn’t a common trait.

They make complex relationships easy to understand. Now, you only need to know how to create a Venn diagram in PowerPoint —quite simple!

Download our Free Venn Diagram Template here .

Pie charts are a great way to show different percentages of a whole. They immediately identify the largest and smallest values. This means that they are great options for drawing attention to differences between one group and another.

However, many people misuse pie charts by overpacking them. As a rule, keep the chart to six or fewer sections. That way, the data is striking, not confusing. Then, make the pie chart your own with small, individual details and designs.

Once again, the powerful presentation of data is in simplicity.

Are you considering incorporating it into your presentation? Here’s how to easily add a pie chart in PowerPoint.

Download our Free Pie Chart Template here .

Bubble Charts

Bubble charts playfully present data in an incredibly visual way. But, what makes them so unique? It's easy: they show different values through varying circle sizes.

Squeezed together, the circles also show a holistic viewpoint. Bigger bubbles catch the eye, while small bubbles illustrate how the data breaks down into smaller values. ¿The result? A presentation of data in a visual form.

It can be one of the most graphic ways to represent the spending distribution. For example, you can instantly see your biggest costs or notice how important finances are getting lost in a sea of bubbles. This quick analysis can be incredibly handy.

Download our Free Bubble Chart Template here .

Maps are the go-to solution for presenting geographic information . They help put data in a real-world context. You usually take a blank map and use color for the important areas.

Blocks, circles, or shading represent value. Knowing where certain data is can be crucial. A consistent color scheme makes it easy to show how valuable each section is.

They also work great when paired with other forms of data visualization. For example, you can use pie charts to provide information about offices in different cities around the world or bar charts to compare revenue in different locations.

Download our Free World Map Template here .

If you want to display chronological data, you must use a timeline. It’s the most effective and space-efficient way to show time passage.

They make it easy for your audience to understand the sequence of events with clear and concise visuals.

You can use timelines to show your company’s history or significant events that impacted your business. Like maps, you can easily mix them with other types of data visuals. This characteristic allows you to create engaging presentations that tell a comprehensive story.

At this point, it's a matter of understanding how to add a timeline correctly in PowerPoint . Spoiler: it's incredibly easy.

Download our Free Timeline Chart Template here .

Flowcharts, like timelines, represent a succession of events. The main difference is that timelines have determined start and finish points and specific dates. Flowcharts, on the other hand, show the passing from one step to the next.

They are great for showing processes and info that need to be in a specific order. They can also help you communicate cause-and-effect information in a visually engaging way.

Their best feature is that (unlike timelines) they can also be circular, meaning this is a recurrent process. All you need now is to become familiar with creating a flowchart in PowerPoint .

Download our Free Flowchart Template here .

5 Tips for data visualization in PowerPoint

Knowing how to present data in PowerPoint presentations is not hard, but it takes time to master it. After all, practice makes perfect!

I've gathered insights from our 200+ expert designers , and here are the top five tips they suggest for enhancing your data presentations!

1. Keep it simple

Don’t overload your audience with information. Let the data speak for itself. If you write text below a chart, keep it minimalist and highlight the key figures. The important thing in a presentation is displaying data in a clear and digestible way.

Put all the heavy facts and figures in a report, but never on a PowerPoint slide.

You can even avoid charts altogether to keep it as simple as possible. And don't get me wrong. We've already covered that charts are the way to go for presenting data in PowerPoint, but there are a few exceptions.

This begs the question: when shouldn't you use charts in PowerPoint? The answer is quite short. If your data is simple or doesn't add much value to your presentation, you might want to skip using charts.

2. Be original

One of the best ways to make your data impactful is originality. Take time to think about how you could present information uniquely. Think of a whole new concept and play around with it. Even if it’s not yet perfect, people will appreciate the effort to be original.

Experiment with creative ways to present your data, adding storytelling techniques , unique design elements, or interactive features. This approach can make the data more appealing and captivating for your audience.

You can even mix up how to present data in PowerPoint. Instead of just one format, consider using two different types of data presentation on a single slide. For instance, try placing a bar chart on the left and a pie chart showcasing different data on the right.

3. Focus on your brand

Keeping your presentation on-brand can genuinely make you stand out from the crowd! Even if you just focus on your brand’s color scheme, it will make your presentation look more polished and professional. 

Have fun experimenting with data visualization tools to ensure they match your company’s products and services. What makes you different from others?

Add your brand's style into your visualization to ensure brand consistency and recognition. Use colors, fonts, and logos aligned with your company's image.

You can even make a presentation that more subtly reflects your brand. Think of what values you want to associate with your company and how you can display these in your presentation design.

4. Highlight key information

Not distracting your audience nicely brings us to our third point: Highlight key information. Being detailed and informative is important, but grabbing and keeping the audience's attention is crucial.

Presenting numbers in PowerPoint can be difficult, but it doesn’t must be. Make your audience listen to the bigger message of your words, not just the exact details. All the smaller particulars can be confirmed later.

Your listeners don’t want to know the facts and figures to the nearest decimal. They want the whole number, which is easy to spot and understand.

The meaning of the number is more important than its numerical value. Is it high or low? Positive or negative? Good or bad for business? These are the questions to which you want the answers to be clear.

Using colors is an excellent way to work with this. Colors are also a great visual tool to showcase contrast. For example, when you're working on a graph to display your revenue, you can showcase expenses in red and earnings in green. This kind of color-coding will make your data visualization clear from first sight!

5. Use Templates!

Presentation templates can be your best friend when you want to present data effectively in PowerPoint.

They offer pre-designed layouts and styles that can ensure consistency throughout your presentation. Templates allow you to adjust colors, fonts, and layouts to match your branding or personal preferences.

Microsoft Office has its own library of templates, but you can also find some pretty amazing ones online. Take some extra time to search and pick one that truly fits your needs and brand. 

¿The good news? Our Templates by 24Slides platform has hundreds of PowerPoint chart templates, all completely free for you to use . You can even download different templates and mix and match slides to make the perfect deck. All are entirely editable, so you can add your own data and forget about design.

If you liked the look of some examples in this article, you might be in luck! Most are part of these, and you can also find them on our Templates platform.

In this article, I've shown why knowing how to present data efficiently in PowerPoint is crucial. Data visualization tools are a must to ensure your message is clear and that it sticks with your audience.

However, achieving results that really stand out could be a huge challenge for beginners.  So, If you want to save time and effort on the learning curve of presenting data in PowerPoint, you can always trust professionals!

With 10+ years of experience and more than 200 designers worldwide, we are the world’s largest presentation design company across the globe.

24Slides' professional PowerPoint designers work with businesses worldwide, helping them transform their presentations from ‘okay’ to ‘spectacular.’ With each presentation, we're crafting a powerful tool to captivate audiences and convey messages effectively!

Looking to boost your PowerPoint game? Check out this content:

• PowerPoint 101: The Ultimate Guide for Beginners
• How to Create the Perfect B2B Sales Presentation
• The Ultimate Brand Identity Presentation Guide [FREE PPT Template]
• 7 Essential Storytelling Techniques for your Business Presentation
• The Cost of PowerPoint Presentations: Discover the hidden expenses you might overlook!

Create professional presentations online

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Data presentation: A comprehensive guide

Learn how to create data presentation effectively and communicate your insights in a way that is clear, concise, and engaging.

Raja Bothra

Building presentations

Hey there, fellow data enthusiast!

Welcome to our comprehensive guide on data presentation.

Whether you're an experienced presenter or just starting, this guide will help you present your data like a pro. We'll dive deep into what data presentation is, why it's crucial, and how to master it. So, let's embark on this data-driven journey together.

What is data presentation?

Data presentation is the art of transforming raw data into a visual format that's easy to understand and interpret. It's like turning numbers and statistics into a captivating story that your audience can quickly grasp. When done right, data presentation can be a game-changer, enabling you to convey complex information effectively.

Why are data presentations important?

Imagine drowning in a sea of numbers and figures. That's how your audience might feel without proper data presentation. Here's why it's essential:

• Clarity : Data presentations make complex information clear and concise.
• Engagement : Visuals, such as charts and graphs, grab your audience's attention.
• Comprehension : Visual data is easier to understand than long, numerical reports.
• Decision-making : Well-presented data aids informed decision-making.
• Impact : It leaves a lasting impression on your audience.

Types of data presentation:

Now, let's delve into the diverse array of data presentation methods, each with its own unique strengths and applications. We have three primary types of data presentation, and within these categories, numerous specific visualization techniques can be employed to effectively convey your data.

1. Textual presentation

Textual presentation harnesses the power of words and sentences to elucidate and contextualize your data. This method is commonly used to provide a narrative framework for the data, offering explanations, insights, and the broader implications of your findings. It serves as a foundation for a deeper understanding of the data's significance.

2. Tabular presentation

Tabular presentation employs tables to arrange and structure your data systematically. These tables are invaluable for comparing various data groups or illustrating how data evolves over time. They present information in a neat and organized format, facilitating straightforward comparisons and reference points.

3. Graphical presentation

Graphical presentation harnesses the visual impact of charts and graphs to breathe life into your data. Charts and graphs are powerful tools for spotlighting trends, patterns, and relationships hidden within the data. Let's explore some common graphical presentation methods:

• Bar charts: They are ideal for comparing different categories of data. In this method, each category is represented by a distinct bar, and the height of the bar corresponds to the value it represents. Bar charts provide a clear and intuitive way to discern differences between categories.
• Pie charts: It excel at illustrating the relative proportions of different data categories. Each category is depicted as a slice of the pie, with the size of each slice corresponding to the percentage of the total value it represents. Pie charts are particularly effective for showcasing the distribution of data.
• Line graphs: They are the go-to choice when showcasing how data evolves over time. Each point on the line represents a specific value at a particular time period. This method enables viewers to track trends and fluctuations effortlessly, making it perfect for visualizing data with temporal dimensions.
• Scatter plots: They are the tool of choice when exploring the relationship between two variables. In this method, each point on the plot represents a pair of values for the two variables in question. Scatter plots help identify correlations, outliers, and patterns within data pairs.

The selection of the most suitable data presentation method hinges on the specific dataset and the presentation's objectives. For instance, when comparing sales figures of different products, a bar chart shines in its simplicity and clarity. On the other hand, if your aim is to display how a product's sales have changed over time, a line graph provides the ideal visual narrative.

Additionally, it's crucial to factor in your audience's level of familiarity with data presentations. For a technical audience, more intricate visualization methods may be appropriate. However, when presenting to a general audience, opting for straightforward and easily understandable visuals is often the wisest choice.

In the world of data presentation, choosing the right method is akin to selecting the perfect brush for a masterpiece. Each tool has its place, and understanding when and how to use them is key to crafting compelling and insightful presentations. So, consider your data carefully, align your purpose, and paint a vivid picture that resonates with your audience.

What to include in data presentation?

When creating your data presentation, remember these key components:

• Data points : Clearly state the data points you're presenting.
• Comparison : Highlight comparisons and trends in your data.
• Graphical methods : Choose the right chart or graph for your data.
• Infographics : Use visuals like infographics to make information more digestible.
• Numerical values : Include numerical values to support your visuals.
• Qualitative information : Explain the significance of the data.
• Source citation : Always cite your data sources.

How to structure an effective data presentation?

Creating a well-structured data presentation is not just important; it's the backbone of a successful presentation. Here's a step-by-step guide to help you craft a compelling and organized presentation that captivates your audience:

1. Know your audience

Understanding your audience is paramount. Consider their needs, interests, and existing knowledge about your topic. Tailor your presentation to their level of understanding, ensuring that it resonates with them on a personal level. Relevance is the key.

2. Have a clear message

Every effective data presentation should convey a clear and concise message. Determine what you want your audience to learn or take away from your presentation, and make sure your message is the guiding light throughout your presentation. Ensure that all your data points align with and support this central message.

3. Tell a compelling story

Human beings are naturally wired to remember stories. Incorporate storytelling techniques into your presentation to make your data more relatable and memorable. Your data can be the backbone of a captivating narrative, whether it's about a trend, a problem, or a solution. Take your audience on a journey through your data.

4. Leverage visuals

Visuals are a powerful tool in data presentation. They make complex information accessible and engaging. Utilize charts, graphs, and images to illustrate your points and enhance the visual appeal of your presentation. Visuals should not just be an accessory; they should be an integral part of your storytelling.

5. Be clear and concise

Avoid jargon or technical language that your audience may not comprehend. Use plain language and explain your data points clearly. Remember, clarity is king. Each piece of information should be easy for your audience to digest.

6. Practice your delivery

Practice makes perfect. Rehearse your presentation multiple times before the actual delivery. This will help you deliver it smoothly and confidently, reducing the chances of stumbling over your words or losing track of your message.

A basic structure for an effective data presentation

Armed with a comprehensive comprehension of how to construct a compelling data presentation, you can now utilize this fundamental template for guidance:

In the introduction, initiate your presentation by introducing both yourself and the topic at hand. Clearly articulate your main message or the fundamental concept you intend to communicate.

Moving on to the body of your presentation, organize your data in a coherent and easily understandable sequence. Employ visuals generously to elucidate your points and weave a narrative that enhances the overall story. Ensure that the arrangement of your data aligns with and reinforces your central message.

As you approach the conclusion, succinctly recapitulate your key points and emphasize your core message once more. Conclude by leaving your audience with a distinct and memorable takeaway, ensuring that your presentation has a lasting impact.

Additional tips for enhancing your data presentation

To take your data presentation to the next level, consider these additional tips:

• Consistent design : Maintain a uniform design throughout your presentation. This not only enhances visual appeal but also aids in seamless comprehension.
• High-quality visuals : Ensure that your visuals are of high quality, easy to read, and directly relevant to your topic.
• Concise text : Avoid overwhelming your slides with excessive text. Focus on the most critical points, using visuals to support and elaborate.
• Anticipate questions : Think ahead about the questions your audience might pose. Be prepared with well-thought-out answers to foster productive discussions.

By following these guidelines, you can structure an effective data presentation that not only informs but also engages and inspires your audience. Remember, a well-structured presentation is the bridge that connects your data to your audience's understanding and appreciation.

Do’s and don'ts on a data presentation

• Use visuals : Incorporate charts and graphs to enhance understanding.
• Keep it simple : Avoid clutter and complexity.
• Highlight key points : Emphasize crucial data.
• Engage the audience : Encourage questions and discussions.
• Practice : Rehearse your presentation.

Don'ts:

• Overload with data : Less is often more; don't overwhelm your audience.
• Fit Unrelated data : Stay on topic; don't include irrelevant information.
• Neglect the audience : Ensure your presentation suits your audience's level of expertise.
• Read word-for-word : Avoid reading directly from slides.
• Lose focus : Stick to your presentation's purpose.

Summarizing key takeaways

• Definition : Data presentation is the art of visualizing complex data for better understanding.
• Importance : Data presentations enhance clarity, engage the audience, aid decision-making, and leave a lasting impact.
• Types : Textual, Tabular, and Graphical presentations offer various ways to present data.
• Choosing methods : Select the right method based on data, audience, and purpose.
• Components : Include data points, comparisons, visuals, infographics, numerical values, and source citations.
• Structure : Know your audience, have a clear message, tell a compelling story, use visuals, be concise, and practice.
• Do's and don'ts : Do use visuals, keep it simple, highlight key points, engage the audience, and practice. Don't overload with data, include unrelated information, neglect the audience's expertise, read word-for-word, or lose focus.

FAQ's on a data presentation

1. what is data presentation, and why is it important in 2024.

Data presentation is the process of visually representing data sets to convey information effectively to an audience. In an era where the amount of data generated is vast, visually presenting data using methods such as diagrams, graphs, and charts has become crucial. By simplifying complex data sets, presentation of the data may helps your audience quickly grasp much information without drowning in a sea of chart's, analytics, facts and figures.

2. What are some common methods of data presentation?

There are various methods of data presentation, including graphs and charts, histograms, and cumulative frequency polygons. Each method has its strengths and is often used depending on the type of data you're using and the message you want to convey. For instance, if you want to show data over time, try using a line graph. If you're presenting geographical data, consider to use a heat map.

3. How can I ensure that my data presentation is clear and readable?

To ensure that your data presentation is clear and readable, pay attention to the design and labeling of your charts. Don't forget to label the axes appropriately, as they are critical for understanding the values they represent. Don't fit all the information in one slide or in a single paragraph. Presentation software like Prezent and PowerPoint can help you simplify your vertical axis, charts and tables, making them much easier to understand.

4. What are some common mistakes presenters make when presenting data?

One common mistake is trying to fit too much data into a single chart, which can distort the information and confuse the audience. Another mistake is not considering the needs of the audience. Remember that your audience won't have the same level of familiarity with the data as you do, so it's essential to present the data effectively and respond to questions during a Q&A session.

5. How can I use data visualization to present important data effectively on platforms like LinkedIn?

When presenting data on platforms like LinkedIn, consider using eye-catching visuals like bar graphs or charts. Use concise captions and e.g., examples to highlight the single most important information in your data report. Visuals, such as graphs and tables, can help you stand out in the sea of textual content, making your data presentation more engaging and shareable among your LinkedIn connections.

Create your data presentation with prezent

Prezent can be a valuable tool for creating data presentations. Here's how Prezent can help you in this regard:

• Time savings : Prezent saves up to 70% of presentation creation time, allowing you to focus on data analysis and insights.
• On-brand consistency : Ensure 100% brand alignment with Prezent's brand-approved designs for professional-looking data presentations.
• Effortless collaboration : Real-time sharing and collaboration features make it easy for teams to work together on data presentations.
• Data storytelling : Choose from 50+ storylines to effectively communicate data insights and engage your audience.
• Personalization : Create tailored data presentations that resonate with your audience's preferences, enhancing the impact of your data.

In summary, Prezent streamlines the process of creating data presentations by offering time-saving features, ensuring brand consistency, promoting collaboration, and providing tools for effective data storytelling. Whether you need to present data to clients, stakeholders, or within your organization, Prezent can significantly enhance your presentation-making process.

So, go ahead, present your data with confidence, and watch your audience be wowed by your expertise.

Thank you for joining us on this data-driven journey. Stay tuned for more insights, and remember, data presentation is your ticket to making numbers come alive! Sign up for our free trial or book a demo ! ‍

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It is the simplest form of data Presentation often used in schools or universities to provide a clearer picture to students, who are better able to capture the concepts effectively through a pictorial Presentation of simple data.

2. Column chart

It is a simplified version of the pictorial Presentation which involves the management of a larger amount of data being shared during the presentations and providing suitable clarity to the insights of the data.

3. Pie Charts

Pie charts provide a very descriptive & a 2D depiction of the data pertaining to comparisons or resemblance of data in two separate fields.

4. Bar charts

A bar chart that shows the accumulation of data with cuboid bars with different dimensions & lengths which are directly proportionate to the values they represent. The bars can be placed either vertically or horizontally depending on the data being represented.

5. Histograms

It is a perfect Presentation of the spread of numerical data. The main differentiation that separates data graphs and histograms are the gaps in the data graphs.

6. Box plots

Box plot or Box-plot is a way of representing groups of numerical data through quartiles. Data Presentation is easier with this style of graph dealing with the extraction of data to the minutes of difference.

Map Data graphs help you with data Presentation over an area to display the areas of concern. Map graphs are useful to make an exact depiction of data over a vast case scenario.

All these visual presentations share a common goal of creating meaningful insights and a platform to understand and manage the data in relation to the growth and expansion of one’s in-depth understanding of data & details to plan or execute future decisions or actions.

Importance of Data Presentation

Data Presentation could be both can be a deal maker or deal breaker based on the delivery of the content in the context of visual depiction.

Data Presentation tools are powerful communication tools that can simplify the data by making it easily understandable & readable at the same time while attracting & keeping the interest of its readers and effectively showcase large amounts of complex data in a simplified manner.

If the user can create an insightful presentation of the data in hand with the same sets of facts and figures, then the results promise to be impressive.

There have been situations where the user has had a great amount of data and vision for expansion but the presentation drowned his/her vision.

To impress the higher management and top brass of a firm, effective presentation of data is needed.

Data Presentation helps the clients or the audience to not spend time grasping the concept and the future alternatives of the business and to convince them to invest in the company & turn it profitable both for the investors & the company.

Although data presentation has a lot to offer, the following are some of the major reason behind the essence of an effective presentation:-

• Many consumers or higher authorities are interested in the interpretation of data, not the raw data itself. Therefore, after the analysis of the data, users should represent the data with a visual aspect for better understanding and knowledge.
• The user should not overwhelm the audience with a number of slides of the presentation and inject an ample amount of texts as pictures that will speak for themselves.
• Data presentation often happens in a nutshell with each department showcasing their achievements towards company growth through a graph or a histogram.
• Providing a brief description would help the user to attain attention in a small amount of time while informing the audience about the context of the presentation
• The inclusion of pictures, charts, graphs and tables in the presentation help for better understanding the potential outcomes.
• An effective presentation would allow the organization to determine the difference with the fellow organization and acknowledge its flaws. Comparison of data would assist them in decision making.

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Blog Graphic Design What is Data Visualization? (Definition, Examples, Best Practices)

What is Data Visualization? (Definition, Examples, Best Practices)

Written by: Midori Nediger Jun 05, 2020

Words don’t always paint the clearest picture. Raw data doesn’t always tell the most compelling story. 

The human mind is very receptive to visual information. That’s why data visualization is a powerful tool for communication.    

But if “data visualization” sounds tricky and technical don’t worry—it doesn’t have to be. 

This guide will explain the fundamentals of data visualization in a way that anyone can understand. Included are a ton of examples of different types of data visualizations and when to use them for your reports, presentations, marketing, and more.

Table of Contents

• What is data visualization?

What is data visualization used for?

Types of data visualizations.

• How to present data visually  (for businesses, marketers, nonprofits, and education)
• Data visualization examples

Data visualization is used everywhere. 

Businesses use data visualization for reporting, forecasting, and marketing. 

CREATE THIS REPORT TEMPLATE

Nonprofits use data visualizations to put stories and faces to numbers. 

Source:  Bill and Melinda Gates Foundation

Scholars and scientists use data visualization to illustrate concepts and reinforce their arguments.

CREATE THIS MIND MAP TEMPLATE

Reporters use data visualization to show trends and contextualize stories. 

While data visualizations can make your work more professional, they can also be a lot of fun.

What is data visualization? A simple definition of data visualization:

Data visualization is the visual presentation of data or information. The goal of data visualization is to communicate data or information clearly and effectively to readers. Typically, data is visualized in the form of a chart , infographic , diagram or map. 

The field of data visualization combines both art and data science. While a data visualization can be creative and pleasing to look at, it should also be functional in its visual communication of the data. 

Data, especially a lot of data, can be difficult to wrap your head around. Data visualization can help both you and your audience interpret and understand data. 

Data visualizations often use elements of visual storytelling to communicate a message supported by the data. 

There are many situations where you would want to present data visually. 

Data visualization can be used for:

• Making data engaging and easily digestible
• Identifying trends and outliers within a set of data
• Telling a story found within the data
• Reinforcing an argument or opinion
• Highlighting the important parts of a set of data

Let’s look at some examples for each use case.

1. Make data digestible and easy to understand

Often, a large set of numbers can make us go cross-eyed. It can be difficult to find the significance behind rows of data. 

Data visualization allows us to frame the data differently by using illustrations, charts, descriptive text, and engaging design. Visualization also allows us to group and organize data based on categories and themes, which can make it easier to break down into understandable chunks. 

Related : How to Use Data Visualization in Your Infographics

For example, this infographic breaks down the concept of neuroplasticity in an approachable way:

Source: NICABM

The same goes for complex, specialized concepts. It can often be difficult to break down the information in a way that non-specialists will understand. But an infographic that organizes the information, with visuals, can demystify concepts for novice readers.

CREATE THIS INFOGRAPHIC TEMPLATE

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It’s 2022 already. Marketers, are you still using data from pre-COVID times?

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The report uses data gathered from over 100,000 customers of HubSpot CRM. In addition to that, you’ll also know about the trends in using visuals in content marketing and the impacts of the pandemic on visual content, from 200+ marketers all over the world interviewed by Venngage.

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2. Identify trends and outliers

If you were to sift through raw data manually, it could take ages to notice patterns, trends or outlying data. But by using data visualization tools like charts, you can sort through a lot of data quickly. 

Even better, charts enable you to pick up on trends a lot quicker than you would sifting through numbers.

For example, here’s a simple chart generated by Google Search Console that shows the change in Google searches for “toilet paper”. As you can see, in March 2020 there was a huge increase in searches for toilet paper:

Source: How to Use SEO Data to Fuel Your Content Marketing Strategy in 2020

This chart shows an outlier in the general trend for toilet paper-related Google searches. The reason for the outlier? The outbreak of COVID-19 in North America. With a simple data visualization, we’ve been able to highlight an outlier and hint at a story behind the data. 

Uploading your data into charts, to create these kinds of visuals is easy. While working on your design in the editor, select a chart from the left panel. Open the chart and find the green IMPORT button under the DATA tab. Then upload the CSV file and your chart automatically visualizes the information. 

3. Tell a story within the data

Numbers on their own don’t tend to evoke an emotional response. But data visualization can tell a story that gives significance to the data. 

Designers use techniques like color theory , illustrations, design style and visual cues to appeal to the emotions of readers, put faces to numbers, and introduce a narrative to the data. 

Related : How to Tell a Story With Data (A Guide for Beginners)

For example, here’s an infographic created by World Vision. In the infographics, numbers are visualized using illustrations of cups. While comparing numbers might impress readers, reinforcing those numbers with illustrations helps to make an even greater impact. 

Source: World Vision

Meanwhile, this infographic uses data to draw attention to an often overlooked issue:

Read More:  The Coronavirus Pandemic and the Refugee Crisis

4. Reinforce an argument or opinion

When it comes to convincing people your opinion is right, they often have to see it to believe it. An effective infographic or chart can make your argument more robust and reinforce your creativity. 

For example, you can use a comparison infographic to compare sides of an argument, different theories, product/service options, pros and cons, and more. Especially if you’re blending data types.

5. Highlight an important point in a set of data

Sometimes we use data visualizations to make it easier for readers to explore the data and come to their own conclusions. But often, we use data visualizations to tell a story, make a particular argument, or encourage readers to come to a specific conclusion. 

Designers use visual cues to direct the eye to different places on a page. Visual cues are shapes, symbols, and colors that point to a specific part of the data visualization, or that make a specific part stand out.

For example, in this data visualization, contrasting colors are used to emphasize the difference in the amount of waste sent to landfills versus recycled waste:

Here’s another example. This time, a red circle and an arrow are used to highlight points on the chart where the numbers show a drop: 

Highlighting specific data points helps your data visualization tell a compelling story.

6. Make books, blog posts, reports and videos more engaging

At Venngage, we use data visualization to make our blog posts more engaging for readers. When we write a blog post or share a post on social media, we like to summarize key points from our content using infographics. 

The added benefit of creating engaging visuals like infographics is that it has enabled our site to be featured in publications like The Wall Street Journal , Mashable , Business Insider , The Huffington Post and more. 

That’s because data visualizations are different from a lot of other types of content people consume on a daily basis. They make your brain work. They combine concrete facts and numbers with impactful visual elements. They make complex concepts easier to grasp. 

Here’s an example of an infographic we made that got a lot of media buzz:

Read the Blog Post: Every Betrayal Ever in Game of Thrones

We created this infographic because a bunch of people on our team are big Game of Thrones fans and we wanted to create a visual that would help other fans follow the show. Because we approached a topic that a lot of people cared about in an original way, the infographic got picked up by a bunch of media sites. 

Whether you’re a website looking to promote your content, a journalist looking for an original angle, or a creative building your portfolio, data visualizations can be an effective way to get people’s attention.

Data visualizations can come in many different forms. People are always coming up with new and creative ways to present data visually. 

Generally speaking, data visualizations usually fall under these main categories:

An infographic is a collection of imagery, charts, and minimal text that gives an easy-to-understand overview of a topic. 

While infographics can take many forms, they can typically be categorized by these infographic types:

• Statistical infographics
• Informational infographics
• Timeline infographics
• Process infographics
• Geographic infographics
• Comparison infographics
• Hierarchical infographics
• List infographics
• Resume infographics

Read More: What is an Infographic? Examples, Templates & Design Tips

Charts 

In the simplest terms, a chart is a graphical representation of data. Charts use visual symbols like line, bars, dots, slices, and icons to represent data points. 

Some of the most common types of charts are:

• Bar graphs /charts
• Line charts
• Bubble charts
• Stacked bar charts
• Word clouds
• Pictographs
• Area charts
• Scatter plot charts
• Multi-series charts

The question that inevitably follows is: what type of chart should I use to visualize my data? Does it matter?

Short answer: yes, it matters. Choosing a type of chart that doesn’t work with your data can end up misrepresenting and skewing your data. 

For example: if you’ve been in the data viz biz for a while, then you may have heard some of the controversy surrounding pie charts. A rookie mistake that people often make is using a pie chart when a bar chart would work better. 

Pie charts display portions of a whole. A pie chart works when you want to compare proportions that are substantially different. Like this:

CREATE THIS CHART TEMPLATE

But when your proportions are similar, a pie chart can make it difficult to tell which slice is bigger than the other. That’s why, in most other cases, a bar chart is a safer bet.

Here is a cheat sheet to help you pick the right type of chart for your data:

Want to make better charts? Make engaging charts with Venngage’s Chart Maker .

Related : How to Choose the Best Types of Charts For Your Data

Similar to a chart, a diagram is a visual representation of information. Diagrams can be both two-dimensional and three-dimensional. 

Some of the most common types of diagrams are:

• Venn diagrams
• Tree diagrams
• SWOT analysis
• Fishbone diagrams
• Use case diagrams

Diagrams are used for mapping out processes, helping with decision making, identifying root causes, connecting ideas, and planning out projects.

CREATE THIS DIAGRAM TEMPLATE

Want to make a diagram ? Create a Venn diagram and other visuals using our free Venn Diagram Maker .

A map is a visual representation of an area of land. Maps show physical features of land like regions, landscapes, cities, roads, and bodies of water. 

Source: National Geographic

A common type of map you have probably come across in your travels is a choropleth map . Choropleth maps use different shades and colors to indicate average quantities. 

For example, a population density map uses varying shades to show the difference in population numbers from region to region:

Create your own map for free with Venngage’s Map Maker .

How to present data visually (data visualization best practices)

While good data visualization will communicate data or information clearly and effectively, bad data visualization will do the opposite. Here are some practical tips for how businesses and organizations can use data visualization to communicate information more effectively. 

Not a designer? No problem. Venngage’s Graph Maker  will help you create better graphs in minutes.

1. Avoid distorting the data

This may be the most important point in this whole blog post. While data visualizations are an opportunity to show off your creative design chops, function should never be sacrificed for fashion. 

The chart styles, colors, shapes, and sizing you use all play a role in how the data is interpreted. If you want to present your data accurately and ethically, then you need to take care to ensure that your data visualization does not present the data falsely. 

There are a number of different ways data can be distorted in a chart. Some common ways data can be distorted are:

• Making the baselines something other than 0 to make numbers seem bigger or smaller than they are – this is called “truncating” a graph
• Compressing or expanding the scale of the Y-axis to make a line or bar seem bigger or smaller than it should be
• Cherry picking data so that only the data points you want to include are on a graph (i.e. only telling part of the story)
• Using the wrong type of chart, graph or diagram for your data
• Going against standard, expected data visualization conventions

Because people use data visualizations to reinforce their opinions, you should always read data visualizations with a critical eye. Often enough, writers may be using data visualization to skew the data in a way that supports their opinions, but that may not be entirely truthful.

Read More: 5 Ways Writers Use Graphs To Mislead You

Want to create an engaging line graph? Use Venngage’s Line Graph Maker to create your own in minutes.

2. Avoid cluttering up your design with “chartjunk”

When it comes to best practices for data visualization, we should turn to one of the grandfather’s of data visualization: Edward Tufte. He coined the term “ chartjunk ”, which refers to the use of unnecessary or confusing design elements that skews or obscures the data in a chart. 

Here’s an example of a data visualization that suffers from chartjunk:

Source: ExcelUser

In this example, the image of the coin is distracting for readers trying to interpret the data. Note how the fonts are tiny – almost unreadable. Mistakes like this are common when a designers tries to put style before function. 

Read More : The Worst Infographics of 2020 (With Lessons for 2021)

3. Tell a story with your data

Data visualizations like infographics give you the space to combine data and narrative structure in one page. Visuals like icons and bold fonts let you highlight important statistics and facts.

For example, you could customize this data visualization infographic template to show the benefit of using your product or service (and post it on social media):

USE THIS TEMPLATE

  This data visualization relies heavily on text and icons to tell the story of its data:

This type of infographic is perfect for those who aren’t as comfortable with charts and graphs. It’s also a great way to showcase original research, get social shares and build brand awareness.

4. Combine different types of data visualizations

While you may choose to keep your data visualization simple, combining multiple types of charts and diagrams can help tell a more rounded story.

Don’t be afraid to combine charts, pictograms and diagrams into one infographic. The result will be a data visualization infographic that is engaging and rich in visual data.

Design Tip: This data visualization infographic would be perfect for nonprofits to customize and include in an email newsletter to increase awareness (and donations).

Or take this data visualization that also combines multiple types of charts, pictograms, and images to engage readers. It could work well in a presentation or report on customer research, customer service scores, quarterly performance and much more:

Design Tip: This infographic could work well in a presentation or report on customer research, customer service scores, quarterly performance and much more.

Make your own bar graph in minutes with our free Bar Graph Maker .

5. Use icons to emphasize important points

Icons are perfect for attracting the eye when scanning a page. (Remember: use visual cues!)

If there are specific data points that you want readers to pay attention to, placing an icon beside it will make it more noticeable:

Design Tip: This infographic template would work well on social media to encourage shares and brand awareness.

You can also pair icons with headers to indicate the beginning of a new section.

Meanwhile, this infographic uses icons like bullet points to emphasize and illustrate important points. 

Design Tip: This infographic would make a great sales piece to promote your course or other service.  

6. Use bold fonts to make text information engaging

A challenge people often face when setting out to visualize information is knowing how much text to include. After all, the point of data visualization is that it presents information visually, rather than a page of text. 

Even if you have a lot of text information, you can still create present data visually. Use bold, interesting fonts to make your data exciting. Just make sure that, above all else, your text is still easy to read.

This data visualization uses different fonts for the headers and body text that are bold but clear. This helps integrate the text into the design and emphasizes particular points:

Design Tip: Nonprofits could use this data visualization infographic in a newsletter or on social media to build awareness, but any business could use it to explain the need for their product or service. 

As a general rule of thumb, stick to no more than three different font types in one infographic.

This infographic uses one font for headers, another font for body text, and a third font for accent text. 

Read More: How to Choose Fonts For Your Designs (With Examples)

Design Tip: Venngage has a library of fonts to choose from. If you can’t find the icon you’re looking for , you can always request they be added. Our online editor has a chat box with 24/7 customer support.

7. Use colors strategically in your design

In design, colors are as functional as they are fashionable. You can use colors to emphasize points, categorize information, show movement or progression, and more. 

For example, this chart uses color to categorize data:

Design Tip : This pie chart can actually be customized in many ways. Human resources could provide a monthly update of people hired by department, nonprofits could show a breakdown of how they spent donations and real estate agents could show the average price of homes sold by neighbourhood.

You can also use light colored text and icons on dark backgrounds to make them stand out. Consider the mood that you want to convey with your infographic and pick colors that will reflect that mood. You can also use contrasting colors from your brand color palette.

This infographic template uses a bold combination of pinks and purples to give the data impact:

Read More: How to Pick Colors to Captivate Readers and Communicate Effectively

8. Show how parts make up a whole

It can be difficult to break a big topic down into smaller parts. Data visualization can make it a lot easier for people to conceptualize how parts make up a whole.

Using one focus visual, diagram or chart can convey parts of a whole more effectively than a text list can. Look at how this infographic neatly visualizes how marketers use blogging as part of their strategy:

Design Tip: Human resources could use this graphic to show the results of a company survey. Or consultants could promote their services by showing their success rates.

Or look at how this infographic template uses one focus visual to illustrate the nutritional makeup of a banana:

CREATE THIS FLYER TEMPLATE

9. Focus on one amazing statistic

If you are preparing a presentation, it’s best not to try and cram too many visuals into one slide. Instead, focus on one awe-inspiring statistic and make that the focus of your slide.

Use one focus visual to give the statistic even more impact. Smaller visuals like this are ideal for sharing on social media, like in this example:

Design Tip: You can easily swap out the icon above (of Ontario, Canada) using Venngage’s drag-and-drop online editor and its in-editor library of icons. Click on the template above to get started.

This template also focuses on one key statistic and offers some supporting information in the bar on the side:

10. Optimize your data visualization for mobile

Complex, information-packed infographics are great for spicing up reports, blog posts, handouts, and more. But they’re not always the best for mobile viewing. 

To optimize your data visualization for mobile viewing, use one focus chart or icon and big, legible font. You can create a series of mobile-optimized infographics to share multiple data points in a super original and attention-grabbing way.

For example, this infographic uses concise text and one chart to cut to the core message behind the data:

CREATE THIS SOCIAL MEDIA TEMPLATE

Some amazing data visualization examples

Here are some of the best data visualization examples I’ve come across in my years writing about data viz. 

Evolution of Marketing Infographic

Graphic Design Trends Infographic

Stop Shark Finning Nonprofit Infographic

Source: Ripetungi

Coronavirus Impact on Environment Data Visualization

What Disney Characters Tell Us About Color Theory

World’s Deadliest Animal Infographic

Source: Bill and Melinda Gates Foundation

The Secret Recipe For a Viral Creepypasta

Read More: Creepypasta Study: The Secret Recipe For a Viral Horror Story

The Hero’s Journey Infographic

Read More: What Your 6 Favorite Movies Have in Common

Emotional Self Care Guide Infographic

Source: Carley Schweet

Want to look at more amazing data visualization? Read More: 50+ Infographic Ideas, Examples & Templates for 2020 (For Marketers, Nonprofits, Schools, Healthcare Workers, and more)

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What Is Data Visualization: Brief Theory, Useful Tips and Awesome Examples

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By Al Boicheva

in Insights , Inspiration

3 years ago

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Updated: June 23, 2022

To create data visualization in order to present your data is no longer just a nice to have skill. Now, the skill to effectively sort and communicate your data through charts is a must-have for any business in any field that deals with data. Data visualization helps businesses quickly make sense of complex data and start making decisions based on that data. This is why today we’ll talk about what is data visualization. We’ll discuss how and why does it work, what type of charts to choose in what cases, how to create effective charts, and, of course, end with beautiful examples.

So let’s jump right in. As usual, don’t hesitate to fast-travel to a particular section of your interest.

Article overview: 1. What Does Data Visualization Mean? 2. How Does it Work? 3. When to Use it? 4. Why Use it? 5. Types of Data Visualization 6. Data Visualization VS Infographics: 5 Main Differences 7. How to Create Effective Data Visualization?: 5 Useful Tips 8. Examples of Data Visualization

1. What is Data Visualization?

Data Visualization is a graphic representation of data that aims to communicate numerous heavy data in an efficient way that is easier to grasp and understand . In a way, data visualization is the mapping between the original data and graphic elements that determine how the attributes of these elements vary. The visualization is usually made by the use of charts, lines, or points, bars, and maps.

• Data Viz is a branch of Descriptive statistics but it requires both design, computer, and statistical skills.
• Aesthetics and functionality go hand in hand to communicate complex statistics in an intuitive way.
• Data Viz tools and technologies are essential for making data-driven decisions.
• It’s a fine balance between form and functionality.
• Every STEM field benefits from understanding data.

2. How Does it Work?

If we can see it, our brains can internalize and reflect on it. This is why it’s much easier and more effective to make sense of a chart and see trends than to read a massive document that would take a lot of time and focus to rationalize. We wouldn’t want to repeat the cliche that humans are visual creatures, but it’s a fact that visualization is much more effective and comprehensive.

In a way, we can say that data Viz is a form of storytelling with the purpose to help us make decisions based on data. Such data might include:

• Tracking sales
• Identifying trends
• Identifying changes
• Monitoring goals
• Monitoring results
• Combining data

3. When to Use it?

Data visualization is useful for companies that deal with lots of data on a daily basis. It’s essential to have your data and trends instantly visible. Better than scrolling through colossal spreadsheets. When the trends stand out instantly this also helps your clients or viewers to understand them instead of getting lost in the clutter of numbers.

With that being said, Data Viz is suitable for:

• Annual reports
• Presentations
• Social media micronarratives
• Informational brochures
• Trend-trafficking
• Candlestick chart for financial analysis
• Determining routes

Common cases when data visualization sees use are in sales, marketing, healthcare, science, finances, politics, and logistics.

4. Why Use it?

Short answer: decision making. Data Visualization comes with the undeniable benefits of quickly recognizing patterns and interpret data. More specifically, it is an invaluable tool to determine the following cases.

• Identifying correlations between the relationship of variables.
• Getting market insights about audience behavior.
• Determining value vs risk metrics.
• Monitoring trends over time.
• Examining rates and potential through frequency.
• Ability to react to changes.

5. Types of Data Visualization

As you probably already guessed, Data Viz is much more than simple pie charts and graphs styled in a visually appealing way. The methods that this branch uses to visualize statistics include a series of effective types.

Map visualization is a great method to analyze and display geographically related information and present it accurately via maps. This intuitive way aims to distribute data by region. Since maps can be 2D or 3D, static or dynamic, there are numerous combinations one can use in order to create a Data Viz map.

COVID-19 Spending Data Visualization POGO by George Railean

The most common ones, however, are:

• Regional Maps: Classic maps that display countries, cities, or districts. They often represent data in different colors for different characteristics in each region.
• Line Maps: They usually contain space and time and are ideal for routing, especially for driving or taxi routes in the area due to their analysis of specific scenes.
• Point Maps: These maps distribute data of geographic information. They are ideal for businesses to pinpoint the exact locations of their buildings in a region.
• Heat Maps: They indicate the weight of a geographical area based on a specific property. For example, a heat map may distribute the saturation of infected people by area.

Charts present data in the form of graphs, diagrams, and tables. They are often confused with graphs since graphs are indeed a subcategory of charts. However, there is a small difference: graphs show the mathematical relationship between groups of data and is only one of the chart methods to represent data.

Infographic Data Visualization by Madeline VanRemmen

With that out of the way, let’s talk about the most basic types of charts in data visualization.

They use a series of bars that illustrate data development.  They are ideal for lighter data and follow trends of no more than three variables or else, the bars become cluttered and hard to comprehend. Ideal for year-on-year comparisons and monthly breakdowns.

These familiar circular graphs divide data into portions. The bigger the slice, the bigger the portion. They are ideal for depicting sections of a whole and their sum must always be 100%. Avoid pie charts when you need to show data development over time or lack a value for any of the portions. Doughnut charts have the same use as pie charts.

They use a line or more than one lines that show development over time. It allows tracking multiple variables at the same time. A great example is tracking product sales by a brand over the years. Area charts have the same use as line charts.

Scatter Plot

These charts allow you to see patterns through data visualization. They have an x-axis and a y-axis for two different values. For example, if your x-axis contains information about car prices while the y-axis is about salaries, the positive or negative relationship will tell you about what a person’s car tells about their salary.

Unlike the charts we just discussed, tables show data in almost a raw format. They are ideal when your data is hard to present visually and aim to show specific numerical data that one is supposed to read rather than visualize.

Data Visualisation | To bee or not to bee by Aishwarya Anand Singh

For example, charts are perfect to display data about a particular illness over a time period in a particular area, but a table comes to better use when you also need to understand specifics such as causes, outcomes, relapses, a period of treatment, and so on.

6. Data Visualization VS Infographics

5 main differences.

They are not that different as both visually represent data. It is often you search for infographics and find images titled Data Visualization and the other way around. In many cases, however, these titles aren’t misleading. Why is that?

• Data visualization is made of just one element. It could be a map, a chart, or a table. Infographics , on the other hand, often include multiple Data Viz elements.
• Unlike data visualizations that can be simple or extremely complex and heavy, infographics are simple and target wider audiences. The latter is usually comprehensible even to people outside of the field of research the infographic represents.
• Interestingly enough, data Viz doesn’t offer narratives and conclusions, it’s a tool and basis for reaching those. While infographics, in most cases offer a story and a narrative. For example, a data visualization map may have the title “Air pollution saturation by region”, while an infographic with the same data would go “Areas A and B are the most polluted in Country C”.
• Data visualizations can be made in Excel or use other tools that automatically generate the design unless they are set for presentation or publishing. The aesthetics of infographics , however, are of great importance and the designs must be appealing to wider audiences.
• In terms of interaction, data visualizations often offer interactive charts, especially in an online form. Infographics, on the other hand, rarely have interaction and are usually static images.

While on topic, you could also be interested to check out these 50 engaging infographic examples that make complex data look great.

7. Tips to Create Effective Data Visualization

The process is naturally similar to creating Infographics and it revolves around understanding your data and audience. To be more precise, these are the main steps and best practices when it comes to preparing an effective visualization of data for your viewers to instantly understand.

1. Do Your Homework

Preparation is half the work already done. Before you even start visualizing data, you have to be sure you understand that data to the last detail.

Knowing your audience is undeniable another important part of the homework, as different audiences process information differently. Who are the people you’re visualizing data for? How do they process visual data? Is it enough to hand them a single pie chart or you’ll need a more in-depth visual report?

The third part of preparing is to determine exactly what you want to communicate to the audience. What kind of information you’re visualizing and does it reflect your goal?

And last, think about how much data you’ll be working with and take it into account.

2. Choose the Right Type of Chart

In a previous section, we listed the basic chart types that find use in data visualization. To determine best which one suits your work, there are a few things to consider.

• How many variables will you have in a chart?
• How many items will you place for each of your variables?
• What will be the relation between the values (time period, comparison, distributions, etc.)

With that being said, a pie chart would be ideal if you need to present what portions of a whole takes each item. For example, you can use it to showcase what percent of the market share takes a particular product. Pie charts, however, are unsuitable for distributions, comparisons, and following trends through time periods. Bar graphs, scatter plots,s and line graphs are much more effective in those cases.

Another example is how to use time in your charts. It’s way more accurate to use a horizontal axis because time should run left to right. It’s way more visually intuitive.

3. Sort your Data

Start with removing every piece of data that does not add value and is basically excess for the chart. Sometimes, you have to work with a huge amount of data which will inevitably make your chart pretty complex and hard to read. Don’t hesitate to split your information into two or more charts. If that won’t work for you, you could use highlights or change the entire type of chart with something that would fit better.

Tip: When you use bar charts and columns for comparison, sort the information in an ascending or a descending way by value instead of alphabetical order.

4. Use Colors to Your Advantage

In every form of visualization, colors are your best friend and the most powerful tool. They create contrasts, accents, and emphasis and lead the eye intuitively. Even here, color theory is important.

When you design your chart, make sure you don’t use more than 5 or 6 colors. Anything more than that will make your graph overwhelming and hard to read for your viewers. However, color intensity is a different thing that you can use to your advantage. For example, when you compare the same concept in different periods of time, you could sort your data from the lightest shade of your chosen color to its darker one. It creates a strong visual progression, proper to your timeline.

Things to consider when you choose colors:

• Different colors for different categories.
• A consistent color palette for all charts in a series that you will later compare.
• It’s appropriate to use color blind-friendly palettes.

5. Get Inspired

Always put your inspiration to work when you want to be at the top of your game. Look through examples, infographics, and other people’s work and see what works best for each type of data you need to implement.

This Twitter account Data Visualization Society is a great way to start. In the meantime, we’ll also handpick some amazing examples that will get you in the mood to start creating the visuals for your data.

8. Examples for Data Visualization

As another art form, Data Viz is a fertile ground for some amazing well-designed graphs that prove that data is beautiful. Now let’s check out some.

Dark Souls III Experience Data

We start with Meng Hsiao Wei’s personal project presenting his experience with playing Dark Souls 3. It’s a perfect example that infographics and data visualization are tools for personal designs as well. The research is pretty massive yet very professionally sorted into different types of charts for the different concepts. All data visualizations are made with the same color palette and look great in infographics.

My dark souls 3 playing data by Meng Hsiao Wei

Greatest Movies of all Time

Katie Silver has compiled a list of the 100 greatest movies of all time based on critics and crowd reviews. The visualization shows key data points for every movie such as year of release, oscar nominations and wins, budget, gross, IMDB score, genre, filming location, setting of the film, and production studio. All movies are ordered by the release date.

100 Greatest Movies Data Visualization by Katie Silver

The Most Violent Cities

Federica Fragapane shows data for the 50 most violent cities in the world in 2017. The items are arranged on a vertical axis based on population and ordered along the horizontal axis according to the homicide rate.

The Most Violent Cities by Federica Fragapane

Family Businesses as Data

These data visualizations and illustrations were made by Valerio Pellegrini for Perspectives Magazine. They show a pie chart with sector breakdown as well as a scatter plot for contribution for employment.

PERSPECTIVES MAGAZINE – Family Businesses by Valerio Pellegrini

Orbit Map of the Solar System

The map shows data on the orbits of more than 18000 asteroids in the solar system. Each asteroid is shown at its position on New Years’ Eve 1999, colored by type of asteroid.

An Orbit Map of the Solar System by Eleanor Lutz

The Semantics Of Headlines

Katja Flükiger has a take on how headlines tell the story. The data visualization aims to communicate how much is the selling influencing the telling. The project was completed at Maryland Institute College of Art to visualize references to immigration and color-coding the value judgments implied by word choice and context.

The Semantics of Headlines by Katja Flükiger

Moon and Earthquakes

This data visualization works on answering whether the moon is responsible for earthquakes. The chart features the time and intensity of earthquakes in response to the phase and orbit location of the moon.

Moon and Earthquakes by Aishwarya Anand Singh

Dawn of the Nanosats

The visualization shows the satellites launched from 2003 to 2015. The graph represents the type of institutions focused on projects as well as the nations that financed them. On the left, it is shown the number of launches per year and satellite applications.

WIRED UK – Dawn of the by Nanosats by Valerio Pellegrini

Final Words

Data visualization is not only a form of science but also a form of art. Its purpose is to help businesses in any field quickly make sense of complex data and start making decisions based on that data. To make your graphs efficient and easy to read, it’s all about knowing your data and audience. This way you’ll be able to choose the right type of chart and use visual techniques to your advantage.

You may also be interested in some of these related articles:

• Infographics for Marketing: How to Grab and Hold the Attention
• 12 Animated Infographics That Will Engage Your Mind from Start to Finish
• 50 Engaging Infographic Examples That Make Complex Ideas Look Great
• Good Color Combinations That Go Beyond Trends: Inspirational Examples and Ideas

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Al Boicheva

Al is an illustrator at GraphicMama with out-of-the-box thinking and a passion for anything creative. In her free time, you will see her drooling over tattoo art, Manga, and horror movies.

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17 Data Visualization Techniques All Professionals Should Know

• 17 Sep 2019

There’s a growing demand for business analytics and data expertise in the workforce. But you don’t need to be a professional analyst to benefit from data-related skills.

Becoming skilled at common data visualization techniques can help you reap the rewards of data-driven decision-making , including increased confidence and potential cost savings. Learning how to effectively visualize data could be the first step toward using data analytics and data science to your advantage to add value to your organization.

Several data visualization techniques can help you become more effective in your role. Here are 17 essential data visualization techniques all professionals should know, as well as tips to help you effectively present your data.

Access your free e-book today.

What Is Data Visualization?

Data visualization is the process of creating graphical representations of information. This process helps the presenter communicate data in a way that’s easy for the viewer to interpret and draw conclusions.

There are many different techniques and tools you can leverage to visualize data, so you want to know which ones to use and when. Here are some of the most important data visualization techniques all professionals should know.

Data Visualization Techniques

The type of data visualization technique you leverage will vary based on the type of data you’re working with, in addition to the story you’re telling with your data .

Here are some important data visualization techniques to know:

• Gantt Chart
• Box and Whisker Plot
• Waterfall Chart
• Scatter Plot
• Pictogram Chart
• Highlight Table
• Bullet Graph
• Choropleth Map
• Network Diagram
• Correlation Matrices

1. Pie Chart

Pie charts are one of the most common and basic data visualization techniques, used across a wide range of applications. Pie charts are ideal for illustrating proportions, or part-to-whole comparisons.

Because pie charts are relatively simple and easy to read, they’re best suited for audiences who might be unfamiliar with the information or are only interested in the key takeaways. For viewers who require a more thorough explanation of the data, pie charts fall short in their ability to display complex information.

2. Bar Chart

The classic bar chart , or bar graph, is another common and easy-to-use method of data visualization. In this type of visualization, one axis of the chart shows the categories being compared, and the other, a measured value. The length of the bar indicates how each group measures according to the value.

One drawback is that labeling and clarity can become problematic when there are too many categories included. Like pie charts, they can also be too simple for more complex data sets.

3. Histogram

Unlike bar charts, histograms illustrate the distribution of data over a continuous interval or defined period. These visualizations are helpful in identifying where values are concentrated, as well as where there are gaps or unusual values.

Histograms are especially useful for showing the frequency of a particular occurrence. For instance, if you’d like to show how many clicks your website received each day over the last week, you can use a histogram. From this visualization, you can quickly determine which days your website saw the greatest and fewest number of clicks.

4. Gantt Chart

Gantt charts are particularly common in project management, as they’re useful in illustrating a project timeline or progression of tasks. In this type of chart, tasks to be performed are listed on the vertical axis and time intervals on the horizontal axis. Horizontal bars in the body of the chart represent the duration of each activity.

Utilizing Gantt charts to display timelines can be incredibly helpful, and enable team members to keep track of every aspect of a project. Even if you’re not a project management professional, familiarizing yourself with Gantt charts can help you stay organized.

5. Heat Map

A heat map is a type of visualization used to show differences in data through variations in color. These charts use color to communicate values in a way that makes it easy for the viewer to quickly identify trends. Having a clear legend is necessary in order for a user to successfully read and interpret a heatmap.

There are many possible applications of heat maps. For example, if you want to analyze which time of day a retail store makes the most sales, you can use a heat map that shows the day of the week on the vertical axis and time of day on the horizontal axis. Then, by shading in the matrix with colors that correspond to the number of sales at each time of day, you can identify trends in the data that allow you to determine the exact times your store experiences the most sales.

6. A Box and Whisker Plot

A box and whisker plot , or box plot, provides a visual summary of data through its quartiles. First, a box is drawn from the first quartile to the third of the data set. A line within the box represents the median. “Whiskers,” or lines, are then drawn extending from the box to the minimum (lower extreme) and maximum (upper extreme). Outliers are represented by individual points that are in-line with the whiskers.

This type of chart is helpful in quickly identifying whether or not the data is symmetrical or skewed, as well as providing a visual summary of the data set that can be easily interpreted.

7. Waterfall Chart

A waterfall chart is a visual representation that illustrates how a value changes as it’s influenced by different factors, such as time. The main goal of this chart is to show the viewer how a value has grown or declined over a defined period. For example, waterfall charts are popular for showing spending or earnings over time.

8. Area Chart

An area chart , or area graph, is a variation on a basic line graph in which the area underneath the line is shaded to represent the total value of each data point. When several data series must be compared on the same graph, stacked area charts are used.

This method of data visualization is useful for showing changes in one or more quantities over time, as well as showing how each quantity combines to make up the whole. Stacked area charts are effective in showing part-to-whole comparisons.

9. Scatter Plot

Another technique commonly used to display data is a scatter plot . A scatter plot displays data for two variables as represented by points plotted against the horizontal and vertical axis. This type of data visualization is useful in illustrating the relationships that exist between variables and can be used to identify trends or correlations in data.

Scatter plots are most effective for fairly large data sets, since it’s often easier to identify trends when there are more data points present. Additionally, the closer the data points are grouped together, the stronger the correlation or trend tends to be.

10. Pictogram Chart

Pictogram charts , or pictograph charts, are particularly useful for presenting simple data in a more visual and engaging way. These charts use icons to visualize data, with each icon representing a different value or category. For example, data about time might be represented by icons of clocks or watches. Each icon can correspond to either a single unit or a set number of units (for example, each icon represents 100 units).

In addition to making the data more engaging, pictogram charts are helpful in situations where language or cultural differences might be a barrier to the audience’s understanding of the data.

11. Timeline

Timelines are the most effective way to visualize a sequence of events in chronological order. They’re typically linear, with key events outlined along the axis. Timelines are used to communicate time-related information and display historical data.

Timelines allow you to highlight the most important events that occurred, or need to occur in the future, and make it easy for the viewer to identify any patterns appearing within the selected time period. While timelines are often relatively simple linear visualizations, they can be made more visually appealing by adding images, colors, fonts, and decorative shapes.

12. Highlight Table

A highlight table is a more engaging alternative to traditional tables. By highlighting cells in the table with color, you can make it easier for viewers to quickly spot trends and patterns in the data. These visualizations are useful for comparing categorical data.

Depending on the data visualization tool you’re using, you may be able to add conditional formatting rules to the table that automatically color cells that meet specified conditions. For instance, when using a highlight table to visualize a company’s sales data, you may color cells red if the sales data is below the goal, or green if sales were above the goal. Unlike a heat map, the colors in a highlight table are discrete and represent a single meaning or value.

13. Bullet Graph

A bullet graph is a variation of a bar graph that can act as an alternative to dashboard gauges to represent performance data. The main use for a bullet graph is to inform the viewer of how a business is performing in comparison to benchmarks that are in place for key business metrics.

In a bullet graph, the darker horizontal bar in the middle of the chart represents the actual value, while the vertical line represents a comparative value, or target. If the horizontal bar passes the vertical line, the target for that metric has been surpassed. Additionally, the segmented colored sections behind the horizontal bar represent range scores, such as “poor,” “fair,” or “good.”

14. Choropleth Maps

A choropleth map uses color, shading, and other patterns to visualize numerical values across geographic regions. These visualizations use a progression of color (or shading) on a spectrum to distinguish high values from low.

Choropleth maps allow viewers to see how a variable changes from one region to the next. A potential downside to this type of visualization is that the exact numerical values aren’t easily accessible because the colors represent a range of values. Some data visualization tools, however, allow you to add interactivity to your map so the exact values are accessible.

15. Word Cloud

A word cloud , or tag cloud, is a visual representation of text data in which the size of the word is proportional to its frequency. The more often a specific word appears in a dataset, the larger it appears in the visualization. In addition to size, words often appear bolder or follow a specific color scheme depending on their frequency.

Word clouds are often used on websites and blogs to identify significant keywords and compare differences in textual data between two sources. They are also useful when analyzing qualitative datasets, such as the specific words consumers used to describe a product.

16. Network Diagram

Network diagrams are a type of data visualization that represent relationships between qualitative data points. These visualizations are composed of nodes and links, also called edges. Nodes are singular data points that are connected to other nodes through edges, which show the relationship between multiple nodes.

There are many use cases for network diagrams, including depicting social networks, highlighting the relationships between employees at an organization, or visualizing product sales across geographic regions.

17. Correlation Matrix

A correlation matrix is a table that shows correlation coefficients between variables. Each cell represents the relationship between two variables, and a color scale is used to communicate whether the variables are correlated and to what extent.

Correlation matrices are useful to summarize and find patterns in large data sets. In business, a correlation matrix might be used to analyze how different data points about a specific product might be related, such as price, advertising spend, launch date, etc.

Other Data Visualization Options

While the examples listed above are some of the most commonly used techniques, there are many other ways you can visualize data to become a more effective communicator. Some other data visualization options include:

• Bubble clouds
• Circle views
• Dendrograms
• Dot distribution maps
• Open-high-low-close charts
• Polar areas
• Radial trees
• Ring Charts
• Sankey diagram
• Span charts
• Streamgraphs
• Wedge stack graphs
• Violin plots

Tips For Creating Effective Visualizations

Creating effective data visualizations requires more than just knowing how to choose the best technique for your needs. There are several considerations you should take into account to maximize your effectiveness when it comes to presenting data.

Related : What to Keep in Mind When Creating Data Visualizations in Excel

One of the most important steps is to evaluate your audience. For example, if you’re presenting financial data to a team that works in an unrelated department, you’ll want to choose a fairly simple illustration. On the other hand, if you’re presenting financial data to a team of finance experts, it’s likely you can safely include more complex information.

Another helpful tip is to avoid unnecessary distractions. Although visual elements like animation can be a great way to add interest, they can also distract from the key points the illustration is trying to convey and hinder the viewer’s ability to quickly understand the information.

Finally, be mindful of the colors you utilize, as well as your overall design. While it’s important that your graphs or charts are visually appealing, there are more practical reasons you might choose one color palette over another. For instance, using low contrast colors can make it difficult for your audience to discern differences between data points. Using colors that are too bold, however, can make the illustration overwhelming or distracting for the viewer.

Related : Bad Data Visualization: 5 Examples of Misleading Data

Visuals to Interpret and Share Information

No matter your role or title within an organization, data visualization is a skill that’s important for all professionals. Being able to effectively present complex data through easy-to-understand visual representations is invaluable when it comes to communicating information with members both inside and outside your business.

There’s no shortage in how data visualization can be applied in the real world. Data is playing an increasingly important role in the marketplace today, and data literacy is the first step in understanding how analytics can be used in business.

Are you interested in improving your analytical skills? Learn more about Business Analytics , our eight-week online course that can help you use data to generate insights and tackle business decisions.

This post was updated on January 20, 2022. It was originally published on September 17, 2019.

About the Author

17 Best Types of Charts and Graphs for Data Visualization [+ Guide]

Published: May 22, 2024

As a writer for the marketing blog, I frequently use various types of charts and graphs to help readers visualize the data I collect and better understand their significance. And trust me, there's a lot of data to present.

In fact, the volume of data in 2025 will be almost double the data we create, capture, copy, and consume today.

This makes data visualization essential for businesses. Different types of graphs and charts can help you:

• Motivate your team to take action.
• Impress stakeholders with goal progress.
• Show your audience what you value as a business.

Data visualization builds trust and can organize diverse teams around new initiatives. So, I'm going to talk about the types of graphs and charts that you can use to grow your business.

And, if you still need a little more guidance by the end of this post, check out our data visualization guide for more information on how to design visually stunning and engaging charts and graphs.  

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Charts vs Graphs: What's the Difference?

A lot of people think charts and graphs are synonymous (I know I did), but they're actually two different things.

Charts visually represent current data in the form of tables and diagrams, but graphs are more numerical in data and show how one variable affects another.

For example, in one of my favorite sitcoms, How I Met Your Mother, Marshall creates a bunch of charts and graphs representing his life. One of these charts is a Venn diagram referencing the song "Cecilia" by Simon and Garfunkle. 

Marshall says, "This circle represents people who are breaking my heart, and this circle represents people who are shaking my confidence daily. Where they overlap? Cecilia."

The diagram is a chart and not a graph because it doesn't track how these people make him feel over time or how these variables are influenced by each other.

It may show where the two types of people intersect but not how they influence one another.

Later, Marshall makes a line graph showing how his friends' feelings about his charts have changed in the time since presenting his "Cecilia diagram.

Note: He calls the line graph a chart on the show, but it's acceptable because the nature of line graphs and charts makes the terms interchangeable. I'll explain later, I promise.

The line graph shows how the time since showing his Cecilia chart has influenced his friends' tolerance for his various graphs and charts. 

Image source

I can't even begin to tell you all how happy I am to reference my favorite HIMYM joke in this post.

Now, let's dive into the various types of graphs and charts. 

Different Types of Graphs for Data Visualization

1. bar graph.

I strongly suggest using a bar graph to avoid clutter when one data label is long or if you have more than 10 items to compare. Also, fun fact: If the example below was vertical it would be a column graph.

Best Use Cases for These Types of Graphs

Bar graphs can help track changes over time. I've found that bar graphs are most useful when there are big changes or to show how one group compares against other groups.

The example above compares the number of customers by business role. It makes it easy to see that there is more than twice the number of customers per role for individual contributors than any other group.

A bar graph also makes it easy to see which group of data is highest or most common.

For example, at the start of the pandemic, online businesses saw a big jump in traffic. So, if you want to look at monthly traffic for an online business, a bar graph would make it easy to see that jump.

Other use cases for bar graphs include:

• Product comparisons.
• Product usage.
• Category comparisons.
• Marketing traffic by month or year.
• Marketing conversions.

Design Best Practices for Bar Graphs

• Use consistent colors throughout the chart, selecting accent colors to highlight meaningful data points or changes over time.

You should also use horizontal labels to improve its readability, and start the y-axis at 0 to appropriately reflect the values in your graph.

2. Line Graph

A line graph reveals trends or progress over time, and you can use it to show many different categories of data. You should use it when you track a continuous data set.

This makes the terms line graphs and line charts interchangeable because the very nature of both is to track how variables impact each other, particularly how something changes over time. Yeah, it confused me, too.

Line graphs help users track changes over short and long periods. Because of this, I find these types of graphs are best for seeing small changes.

Line graphs help me compare changes for more than one group over the same period. They're also helpful for measuring how different groups relate to each other.

A business might use this graph to compare sales rates for different products or services over time.

These charts are also helpful for measuring service channel performance. For example, a line graph that tracks how many chats or emails your team responds to per month.

Design Best Practices for Line Graphs

• Use solid lines only.
• Don't plot more than four lines to avoid visual distractions.
• Use the right height so the lines take up roughly 2/3 of the y-axis' height.

3. Bullet Graph

A bullet graph reveals progress towards a goal, compares this to another measure, and provides context in the form of a rating or performance.

In the example above, the bullet graph shows the number of new customers against a set customer goal. Bullet graphs are great for comparing performance against goals like this.

These types of graphs can also help teams assess possible roadblocks because you can analyze data in a tight visual display.

For example, I could create a series of bullet graphs measuring performance against benchmarks or use a single bullet graph to visualize these KPIs against their goals:

• Customer satisfaction.
• Average order size.
• New customers.

Seeing this data at a glance and alongside each other can help teams make quick decisions.

Bullet graphs are one of the best ways to display year-over-year data analysis. YBullet graphs can also visualize:

• Customer satisfaction scores.
• Customer shopping habits.
• Social media usage by platform.

Design Best Practices for Bullet Graphs

• Use contrasting colors to highlight how the data is progressing.
• Use one color in different shades to gauge progress.

4. Column + Line Graph

Column + line graphs are also called dual-axis charts. They consist of a column and line graph together, with both graphics on the X axis but occupying their own Y axis.

Download our FREE Excel Graph Templates for this graph and more!

Best Use Cases

These graphs are best for comparing two data sets with different measurement units, such as rate and time. 

As a marketer, you may want to track two trends at once.

Design Best Practices 

Use individual colors for the lines and colors to make the graph more visually appealing and to further differentiate the data. 

The Four Basic Types of Charts

Before we get into charts, I want to touch on the four basic chart types that I use the most. 

1. Bar Chart

Bar charts are pretty self-explanatory. I use them to indicate values by the length of bars, which can be displayed horizontally or vertically. Vertical bar charts, like the one below, are sometimes called column charts. 

2. Line Chart 

I use line charts to show changes in values across continuous measurements, such as across time, generations, or categories. For example, the chart below shows the changes in ice cream sales throughout the week.

3. Scatter Plot

A scatter plot uses dotted points to compare values against two different variables on separate axes. It's commonly used to show correlations between values and variables. 

4. Pie Chart

Pie charts are charts that represent data in a circular (pie-shaped) graphic, and each slice represents a percentage or portion of the whole. 

Notice the example below of a household budget. (Which reminds me that I need to set up my own.)

Notice that the percentage of income going to each expense is represented by a slice. 

Different Types of Charts for Data Visualization

To better understand chart types and how you can use them, here's an overview of each:

1. Column Chart

Use a column chart to show a comparison among different items or to show a comparison of items over time. You could use this format to see the revenue per landing page or customers by close date.

Best Use Cases for This Type of Chart

I use both column charts to display changes in data, but I've noticed column charts are best for negative data. The main difference, of course, is that column charts show information vertically while bar charts  show data horizontally.

For example, warehouses often track the number of accidents on the shop floor. When the number of incidents falls below the monthly average, a column chart can make that change easier to see in a presentation.

In the example above, this column chart measures the number of customers by close date. Column charts make it easy to see data changes over a period of time. This means that they have many use cases, including:

• Customer survey data, like showing how many customers prefer a specific product or how much a customer uses a product each day.
• Sales volume, like showing which services are the top sellers each month or the number of sales per week.
• Profit and loss, showing where business investments are growing or falling.

Design Best Practices for Column Charts

• Use horizontal labels to improve readability.
• Start the y-axis at 0 to appropriately reflect the values in your chart .

2. Area Chart

Okay, an area chart is basically a line chart, but I swear there's a meaningful difference.

The space between the x-axis and the line is filled with a color or pattern. It is useful for showing part-to-whole relations, like showing individual sales reps’ contributions to total sales for a year.

It helps me analyze both overall and individual trend information.

Best Use Cases for These Types of Charts

Area charts help show changes over time. They work best for big differences between data sets and help visualize big trends.

For example, the chart above shows users by creation date and life cycle stage.

A line chart could show more subscribers than marketing qualified leads. But this area chart emphasizes how much bigger the number of subscribers is than any other group.

These charts make the size of a group and how groups relate to each other more visually important than data changes over time.

Area charts  can help your business to:

• Visualize which product categories or products within a category are most popular.
• Show key performance indicator (KPI) goals vs. outcomes.
• Spot and analyze industry trends.

Design Best Practices for Area Charts

• Use transparent colors so information isn't obscured in the background.
• Don't display more than four categories to avoid clutter.
• Organize highly variable data at the top of the chart to make it easy to read.

3. Stacked Bar Chart

I suggest using this chart to compare many different items and show the composition of each item you’re comparing.

These charts  are helpful when a group starts in one column and moves to another over time.

For example, the difference between a marketing qualified lead (MQL) and a sales qualified lead (SQL) is sometimes hard to see. The chart above helps stakeholders see these two lead types from a single point of view — when a lead changes from MQL to SQL.

Stacked bar charts are excellent for marketing. They make it simple to add a lot of data on a single chart or to make a point with limited space.

These charts  can show multiple takeaways, so they're also super for quarterly meetings when you have a lot to say but not a lot of time to say it.

Stacked bar charts are also a smart option for planning or strategy meetings. This is because these charts can show a lot of information at once, but they also make it easy to focus on one stack at a time or move data as needed.

You can also use these charts to:

• Show the frequency of survey responses.
• Identify outliers in historical data.
• Compare a part of a strategy to its performance as a whole.

Design Best Practices for Stacked Bar Charts

• Best used to illustrate part-to-whole relationships.
• Use contrasting colors for greater clarity.
• Make the chart scale large enough to view group sizes in relation to one another.

4. Mekko Chart

Also known as a Marimekko chart, this type of chart  can compare values, measure each one's composition, and show data distribution across each one.

It's similar to a stacked bar, except the Mekko's x-axis can capture another dimension of your values — instead of time progression, like column charts often do. In the graphic below, the x-axis compares the cities to one another.

Image Source

I typically use a Mekko chart to show growth, market share, or competitor analysis.

For example, the Mekko chart above shows the market share of asset managers grouped by location and the value of their assets. This chart clarifies which firms manage the most assets in different areas.

It's also easy to see which asset managers are the largest and how they relate to each other.

Mekko charts can seem more complex than other types of charts, so it's best to use these in situations where you want to emphasize scale or differences between groups of data.

Other use cases for Mekko charts include:

• Detailed profit and loss statements.
• Revenue by brand and region.
• Product profitability.
• Share of voice by industry or niche.

Design Best Practices for Mekko Charts

• Vary your bar heights if the portion size is an important point of comparison.
• Don't include too many composite values within each bar. Consider reevaluating your presentation if you have a lot of data.
• Order your bars from left to right in such a way that exposes a relevant trend or message.

5. Pie Chart

Remember, a pie chart represents numbers in percentages, and the total sum of all segments needs to equal 100%.

The image above shows another example of customers by role in the company.

The bar chart  example shows you that there are more individual contributors than any other role. But this pie chart makes it clear that they make up over 50% of customer roles.

Pie charts make it easy to see a section in relation to the whole, so they are good for showing:

• Customer personas in relation to all customers.
• Revenue from your most popular products or product types in relation to all product sales.
• Percent of total profit from different store locations.

Design Best Practices for Pie Charts

• Don't illustrate too many categories to ensure differentiation between slices.
• Ensure that the slice values add up to 100%.
• Order slices according to their size.

6. Scatter Plot Chart

As I said earlier, a scatter plot or scattergram chart will show the relationship between two different variables or reveal distribution trends.

Use this chart when there are many different data points, and you want to highlight similarities in the data set. This is useful when looking for outliers or understanding your data's distribution.

Scatter plots are helpful in situations where you have too much data to see a pattern quickly. They are best when you use them to show relationships between two large data sets.

In the example above, this chart shows how customer happiness relates to the time it takes for them to get a response.

This type of chart  makes it easy to compare two data sets. Use cases might include:

• Employment and manufacturing output.
• Retail sales and inflation.
• Visitor numbers and outdoor temperature.
• Sales growth and tax laws.

Try to choose two data sets that already have a positive or negative relationship. That said, this type of chart  can also make it easier to see data that falls outside of normal patterns.

Design Best Practices for Scatter Plots

• Include more variables, like different sizes, to incorporate more data.
• Start the y-axis at 0 to represent data accurately.
• If you use trend lines, only use a maximum of two to make your plot easy to understand.

7. Bubble Chart

A bubble chart is similar to a scatter plot in that it can show distribution or relationship. There is a third data set shown by the size of the bubble or circle.

In the example above, the number of hours spent online isn't just compared to the user's age, as it would be on a scatter plot chart.

Instead, you can also see how the gender of the user impacts time spent online.

This makes bubble charts useful for seeing the rise or fall of trends over time. It also lets you add another option when you're trying to understand relationships between different segments or categories.

For example, if you want to launch a new product, this chart could help you quickly see your new product's cost, risk, and value. This can help you focus your energies on a low-risk new product with a high potential return.

You can also use bubble charts for:

• Top sales by month and location.
• Customer satisfaction surveys.
• Store performance tracking.
• Marketing campaign reviews.

Design Best Practices for Bubble Charts

• Scale bubbles according to area, not diameter.
• Make sure labels are clear and visible.
• Use circular shapes only.

8. Waterfall Chart

I sometimes use a waterfall chart to show how an initial value changes with intermediate values — either positive or negative — and results in a final value.

Use this chart to reveal the composition of a number. An example of this would be to showcase how different departments influence overall company revenue and lead to a specific profit number.

The most common use case for a funnel chart is the marketing or sales funnel. But there are many other ways to use this versatile chart.

If you have at least four stages of sequential data, this chart can help you easily see what inputs or outputs impact the final results.

For example, a funnel chart can help you see how to improve your buyer journey or shopping cart workflow. This is because it can help pinpoint major drop-off points.

Other stellar options for these types of charts include:

• Deal pipelines.
• Conversion and retention analysis.
• Bottlenecks in manufacturing and other multi-step processes.
• Marketing campaign performance.
• Website conversion tracking.

Design Best Practices for Funnel Charts

• Scale the size of each section to accurately reflect the size of the data set.
• Use contrasting colors or one color in graduated hues, from darkest to lightest, as the size of the funnel decreases.

10. Heat Map

A heat map shows the relationship between two items and provides rating information, such as high to low or poor to excellent. This chart displays the rating information using varying colors or saturation.

Best Use Cases for Heat Maps

In the example above, the darker the shade of green shows where the majority of people agree.

With enough data, heat maps can make a viewpoint that might seem subjective more concrete. This makes it easier for a business to act on customer sentiment.

There are many uses for these types of charts. In fact, many tech companies use heat map tools to gauge user experience for apps, online tools, and website design .

Another common use for heat map charts  is location assessment. If you're trying to find the right location for your new store, these maps can give you an idea of what the area is like in ways that a visit can't communicate.

Heat maps can also help with spotting patterns, so they're good for analyzing trends that change quickly, like ad conversions. They can also help with:

• Competitor research.
• Customer sentiment.
• Sales outreach.
• Campaign impact.
• Customer demographics.

Design Best Practices for Heat Map

• Use a basic and clear map outline to avoid distracting from the data.
• Use a single color in varying shades to show changes in data.
• Avoid using multiple patterns.

11. Gantt Chart

The Gantt chart is a horizontal chart that dates back to 1917. This chart maps the different tasks completed over a period of time.

Gantt charting is one of the most essential tools for project managers. It brings all the completed and uncompleted tasks into one place and tracks the progress of each.

While the left side of the chart displays all the tasks, the right side shows the progress and schedule for each of these tasks.

This chart type allows you to:

• Break projects into tasks.
• Track the start and end of the tasks.
• Set important events, meetings, and announcements.
• Assign tasks to the team and individuals.

I use donut charts for the same use cases as pie charts, but I tend to prefer the former because of the added benefit that the data is easier to read.

Another benefit to donut charts is that the empty center leaves room for extra layers of data, like in the examples above. 

Design Best Practices for Donut Charts 

Use varying colors to better differentiate the data being displayed, just make sure the colors are in the same palette so viewers aren't put off by clashing hues. 

How to Choose the Right Chart or Graph for Your Data

Channels like social media or blogs have multiple data sources, and managing these complex content assets can get overwhelming. What should you be tracking? What matters most?

How do you visualize and analyze the data so you can extract insights and actionable information?

1. Identify your goals for presenting the data.

Before creating any data-based graphics, I ask myself if I want to convince or clarify a point. Am I trying to visualize data that helped me solve a problem? Or am I trying to communicate a change that's happening?

A chart or graph can help compare different values, understand how different parts impact the whole, or analyze trends. Charts and graphs can also be useful for recognizing data that veers away from what you’re used to or help you see relationships between groups.

So, clarify your goals then use them to guide your chart selection.

2. Figure out what data you need to achieve your goal.

Different types of charts and graphs use different kinds of data. Graphs usually represent numerical data, while charts are visual representations of data that may or may not use numbers.

So, while all graphs are a type of chart, not all charts are graphs. If you don't already have the kind of data you need, you might need to spend some time putting your data together before building your chart.

3. Gather your data.

Most businesses collect numerical data regularly, but you may need to put in some extra time to collect the right data for your chart.

Besides quantitative data tools that measure traffic, revenue, and other user data, you might need some qualitative data.

These are some other ways you can gather data for your data visualization:

• Interviews 
• Quizzes and surveys
• Customer reviews
• Reviewing customer documents and records
• Community boards

Fill out the form to get your templates.

4. select the right type of graph or chart..

Choosing the wrong visual aid or defaulting to the most common type of data visualization could confuse your viewer or lead to mistaken data interpretation.

But a chart is only useful to you and your business if it communicates your point clearly and effectively.

Ask yourself the questions below to help find the right chart or graph type.

Download the Excel templates mentioned in the video here.

5 Questions to Ask When Deciding Which Type of Chart to Use

1. do you want to compare values.

Charts and graphs are perfect for comparing one or many value sets, and they can easily show the low and high values in the data sets. To create a comparison chart, use these types of graphs:

• Scatter plot

2. Do you want to show the composition of something?

Use this type of chart to show how individual parts make up the whole of something, like the device type used for mobile visitors to your website or total sales broken down by sales rep.

To show composition, use these charts:

• Stacked bar

3. Do you want to understand the distribution of your data?

Distribution charts help you to understand outliers, the normal tendency, and the range of information in your values.

Use these charts to show distribution:

4. Are you interested in analyzing trends in your data set?

If you want more information about how a data set performed during a specific time, there are specific chart types that do extremely well.

You should choose one of the following:

• Dual-axis line

5. Do you want to better understand the relationship between value sets?

Relationship charts can show how one variable relates to one or many different variables. You could use this to show how something positively affects, has no effect, or negatively affects another variable.

When trying to establish the relationship between things, use these charts:

Featured Resource: The Marketer's Guide to Data Visualization

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14.2 Incorporating Effective Visuals into a Presentation

Learning objectives.

• Recognize the characteristics of effective visual aids.
• Analyze different types of visual aids and appropriate ways to use them.
• Determine how to create original visual aids and how to locate visual aids created by others.

Good communication is a multisensory experience. Children first learning how to read often gravitate toward books with engaging pictures. As adults, we graduate to denser books without pictures, yet we still visualize ideas to help us understand the text. Advertisers favor visual media—television, magazines, and billboards—because they are the best way to hook an audience. Websites rely on color, graphics, icons, and a clear system of visual organization to engage Internet surfers.

Bringing visuals into a presentation adds color, literally and figuratively. There is an art to doing it well. This section covers how to use different kinds of visual aids effectively.

Using Visual Aids: The Basics

Good writers make conscious choices. They understand their purpose and audience. Every decision they make on the page, from organizing an essay to choosing a word with just the right connotations, is made with their purpose and audience in mind.

The same principle applies to visual communication. As a presenter, you choose the following:

• When to show images or video for maximum impact
• Which images will best produce the effect you want
• When to present information using a table, chart, or other graphic
• How much text to include in slides or informational graphics
• How to organize graphics so they present information clearly

Your goal is to use visual media to support and enhance your presentation. At the same time, you must make sure these media do not distract your audience or interfere with getting your point across. Your ideas, not your visuals, should be the focus.

As you develop the visual side of your presentation, you will follow a process much like the process you follow when you write. You will brainstorm ideas, form an organizational plan, develop drafts, and then refine and edit your work. The following sections provide guidelines to help you make good decisions throughout the process.

What Makes Visual Aids Effective?

To help you get a sense of what makes visual media work, think about what does not work. Try to recall occasions when you have witnessed the following visual media failures:

• Websites crammed with so many images, flashing phrases, and clashing colors that they are almost unreadable
• Assembly instructions with illustrations or diagrams that are impossible to follow
• Photographs that are obviously (and badly) altered with photo-editing software
• Distracting typos or other errors in signs, advertisements, or headlines
• Tables, charts, or graphs with tiny, dense text or missing labels

In each case, the problem is that the media creator did not think carefully enough about the purpose and audience. The purpose of images, color, or flashing text on a website is to attract attention. Overusing these elements defeats the purpose because the viewer may become overwhelmed or distracted. Tables, charts, and graphs are intended to simplify complex information, but without clear labels and legible text, they will confuse the audience.

In contrast, effective visual elements are chosen or created with the purpose and audience in mind. Although a photo shoot for a magazine article might result in dozens of images, editors choose those few that work best with the article. Web designers and video game creators have an audience test their products before they are released, to ensure that people will understand how to use them. Understanding the function of different visual aids will help you use them with purpose.

Types of Visual Aids

Visual aids fall into two main categories—images and informational graphics. Images include photographs, illustrations and clip art, and video footage. Informational graphics include tables, charts, bar graphs, and line graphs.

These visual aids serve two purposes: to add emotional impact to your presentation and to organize information more clearly. With that in mind, read to find out how specific types of visual aids achieve those purposes.

Photographs

A striking photograph can capture your audience’s attention far more successfully than words can. Consider including photographs at the beginning or end of your presentation to emphasize your main ideas or to accompany a particularly important point in the body of your presentation. Remember that, as with other types of graphics, less is often more. Two or three well-chosen photographs are more effective than a dozen mediocre ones.

When you choose photographs, ask yourself these questions:

• What purpose does this image serve? Will it surprise the audience? Will it provoke a strong emotional response? Does it support an important point?
• Will this photograph be more effective if shown with only a caption, or does it need additional text?
• Will the audience understand what is happening in the photograph? Is the meaning immediately evident, or does the photo need some context?
• Would editing the image make it more effective? Consider using image-editing software to crop the photo, change the brightness, or make other cosmetic changes. (Do not go overboard, though. A slightly imperfect but authentic image is preferable to one that has been obviously altered.)

To illustrate the sense of helplessness people felt in the midst of tragedy, a student could use a photograph that shows fear, weariness, or defeat on the face of the photograph’s subject.

Figure 14.3

Neil Moralee – On The Scrap Heap . – CC BY-NC-ND 2.0.

Illustrations

Illustrations, such as editorial or political cartoons, serve much the same purpose as photographs. Because an illustration does not capture a moment in time the way a photo does, it may have less impact. However, depending on your topic and the effect you want to achieve, illustrations can still be very useful. Use the same criteria for choosing photographs to help you choose illustrations.

Figure 14.4

Humor Blog – Political Cartoon about Budget Cuts – CC BY 2.0.

The style of an illustration or photograph affects viewers just as the content does. Keep this in mind if you are working with the stock images available in office software programs. Many of these images have a comical tone. This may be fine for some topics—for instance, a presentation on television shows for children. However, if you need to project a more serious tone, make sure you choose images to suit that purpose. Many free (or reasonably priced) image banks are available online.

Video Footage

Even more than photographs, video footage can create a sense of immediacy, especially if your video includes sound. Showing a brief video clip can help your audience feel as if they are present at an important event, connect with a person being interviewed, or better understand a process. Again, ask yourself the following questions to ensure you are using the footage well:

• What purpose does this video serve? (Never rely on video clips just to fill time.)
• How much footage should be shown to achieve your purpose?
• What will need to be explained, before or after showing the video, to ensure that your audience understands its significance?
• Will it be necessary to edit the video to stay within time requirements or to focus on the most important parts?

Informational graphics, such as tables, charts, and graphs, do not provoke the same response that images do. Nevertheless, these graphics can have a powerful impact. Their primary purpose is to organize and simplify information.

Tables are effective when you must classify information and organize it in categories. Tables are an especially good choice when you are presenting qualitative data that are not strictly numerical. Table 14.1 “Example of Qualitative Data Table” was created for a presentation discussing the subprime mortgage crisis. It presents information about people who have held powerful positions both in the government and at one of the investment banking firms involved in the subprime mortgage market.

Table 14.1 Example of Qualitative Data Table

Sources: http://www.rollingstone.com/politics/news/%3Bkw=%5B3351,11459%5D ; http://www.nytimes.com/2008/10/19/business/19gold.html ; http://topics.nytimes.com/top/reference/timestopics/people/p/henry_m_jr_paulson/index.html?inline=nyt-per ; http://topics.nytimes.com/top/reference/timestopics/people/r/robert_e_rubin/index.html?inline=nyt-per , http://www.nytimes.com/2002/12/13/us/man-in-the-news-economic-adviser-from-other-side-of-the-deficit-stephen-friedman.html ; http://news.bbc.co.uk/2/hi/business/342086.stm .

If you are working with numerical information, consider whether a pie chart, bar graph, or line graph might be an effective way to present the content. A table can help you organize numerical information, but it is not the most effective way to emphasize contrasting data or to show changes over time.

Pie charts are useful for showing numerical information in percentages. For example, you can use a pie chart to represent presidential election results by showing what percentage of voters voted for the Democratic presidential candidate, the Republican candidate, and candidates from other political parties.

Figure 14.5

Source: http://www.fec.gov/pubrec/fe2008/2008presgeresults.pdf

Bar graphs work well when you want to show similarities and differences in numerical data. Horizontal or vertical bars help viewers compare data from different groups, different time periods, and so forth. For instance, the bar graph in Figure 14.6 allows the viewer to compare data on the five countries that have won the most Olympic medals since the modern games began in 1924: Norway, the United States, the former Soviet Union, Germany, and Austria. Bar graphs can effectively show trends or patterns in data as well.

Figure 14.6

Source: http://www.nbcolympics.com/medals/all-time-standings/index.html

Line Graphs

Like bar graphs, line graphs show trends in data. Line graphs are usually used to show trends in data over time. For example, the line graph in Figure 14.7 shows changes in the Dow Jones Industrial Average—an economic index based on trading information about thirty large, US-based public companies. This graph shows where the Dow closed at the end of each business day over a period of five days.

Figure 14.7

Source: http://www.google.com/finance/historical?cid=983582&startdate=May+17%2C+2010&enddate=May+21%2C+2010

In this exercise, you will begin to refine your ideas for incorporating media into your presentation. Complete the following steps on your own sheet of paper.

• Revisit the list you brainstormed for Note 14.12 “Exercise 3” in Chapter 14 “Creating Presentations: Sharing Your Ideas” , Section 14.1 “Organizing a Visual Presentation” and the annotated outline you developed for Note 14.17 “Exercise 4” .
• Analyze the two different types of visual aids: images and informational graphics. Identify at least two places in your presentation where you might incorporate visual aids.
• Evaluate the purpose of the visual aid. Does it create emotional impact, or does it organize information? Is the visual effective?
• Determine whether you will be able to create the visual aid yourself or will need to find it.

Creating Original Visual Aids

You will include original visual aids in your presentation to add interest, present complex information or data more clearly, or appeal to your audience’s emotions. You may wish to create some visual aids by hand—for instance, by mounting photographs on poster board for display. More likely, however, you will use computer-generated graphics.

Computer-generated visual aids are easy to create once you learn how to use certain office software. They also offer greater versatility. You can print hard copies and display them large or include them in a handout for your audience. Or, if you are working with presentation software, you can simply insert the graphics in your slides.

Regardless of how you proceed, keep the following guidelines in mind:

• Create visual aids with purpose. Think carefully about how they will enhance your message, and choose a form that is appropriate for your content.
• Strive for quality. You do not need the skills of a professional photographer or designer, but do take time to make sure your visual aids are neat, attractive, and legible. Proofread for errors, too.

Using Software to Create Visual Aids

You can use standard office software to create simple graphics easily. The following guidelines describe how to work with word-processing software and presentation software.

Working with Photographs

Most personal computers come equipped with some basic image-editing software, and many people choose to purchase more advanced programs as well. You can upload photographs from a digital camera (or in some cases, a cell phone) or scan and upload printed photographs. The images can then be edited and incorporated into your presentation. Be sure to save all of your images in one folder for easy access.

Creating Tables

To create a table within a word-processing document consult your software program’s help feature or an online tutorial. Once you have created the table, you can edit and make any additional changes. Be sure that the table has no more than six to seven rows or columns because you do not want to compromise the size of the text or the readability. Aligning with precision will help your table look less crowded. Also, the row and column titles should spell out their contents.

Creating Graphs

Figure 14.8

Pie charts and bar and line graphs can also be created using standard office software. Although you can create these graphics within a document, you will need to work with both your word-processing application and your spreadsheet application to do so. The graph should visually explain the data using colors, titles, and labels. The use of color will help the audience distinguish information; however, avoid colors that are hard on the eyes, such as lime green or hot pink. The title should clearly state what the graph explains. Lastly, avoid using acronyms in the titles and other labels.

Creating Graphics in an Electronic Presentation

If you plan to work only with hard copy graphics during your presentation, you may choose to create them as word-processing documents. However, if you are using presentation software, you will need to choose one of the following options:

• Create your graphics using the presentation software program.
• Create your graphics within another program and import them.

Standard office presentation software allows you to create informational graphics in much the same way you would create them within a word-processing application. Keep the formatting palette, a menu option that allows you to customize the graphic, open while you use the software. The formatting menu provides options for inserting other types of graphics, such as pictures and video. You may insert pictures from an image bank available within the program, or insert images or video from your own desktop files. Shape your use of multimedia in accordance with the message your presentation is trying to convey, the purpose, and your audience.

Creating Visual Aids by Hand

Most of the time, using computer-generated graphics is more efficient than creating them by hand. Using office software programs helps give your graphics a polished appearance while also teaching you skills that are useful in a variety of jobs. However, it may make sense to use hand-created visual aids in some cases—for instance, when showing a 3-D model would be effective. If you follow this route, be sure to devote extra time to making sure your visual aids are neat, legible, and professional.

Flip charts are inexpensive and quick visual aids used during face-to-face presentations. The flip chart can be prepared before, as well as during, the presentation. Each sheet of paper should contain one theme, idea, or sketch and must be penned in large letters to be seen by audience members farthest away from the speaker.

Writing Captions

Any media you incorporate should include a caption or other explanatory text. A caption is a brief, one- to two-sentence description or explanation of a visual image. Make sure your captions are clear, accurate, and to the point. Use full sentences when you write them.

Captions should always be used with photographs, and in some cases, they can be useful for clarifying informational graphics, which represent qualitative data visually. However, informational graphics may not require a caption if the title and labels are sufficiently clear. For other visual media, such as video footage, providing explanatory text before or after the footage will suffice. The important thing is to make sure you always include some explanation of the media.

In this exercise, you will begin to develop visual aids for your presentation. Complete the steps in this exercise—and enjoy the chance to be creative. Working with visuals can be a pleasant way to take a break from the demands of writing.

• Revisit the ideas you developed in Note 14.24 “Exercise 1” . Choose at least two ideas that you can create. ( Note: If you are using software to develop a slideshow presentation, count this as one of your self-created visual aids. Include at least one other self-created visual aid, such as an original photograph, within your slideshow.)
• Get creative! Take your photographs, construct a 3-D model, create informational graphics, or work on your presentation slides. Develop good working drafts.
• After you have completed drafts of your visual aids, set them aside for a while. Then revisit them with a critical eye. First, check any text included with the graphic. Make sure your facts are correct, your words are clear and concise, and your language is free of errors.
• Next, evaluate how well your aids work visually. Are they large enough to be seen and read from a distance? Are captions and labels easy to find? Are photographs of reasonably high quality? Ask someone else for feedback, too.
• Begin making any needed changes. As you proceed through the rest of this section, continue to revisit your work to improve it as needed.

Collaboration

Please share the first version of your visual aids with a classmate. Examine what they have produced. On a separate piece of paper, note both the elements that catch your attention and those that would benefit from clarification. Return and compare notes.

Testing and Evaluating Visual Aids

Regardless of how you create your visual aids, be sure to test-drive them before you deliver your presentation. Edit and proofread them, and if possible, show them to someone who can give you objective feedback. Use the following checklist.

Checklist 14.1

Visual Aid Evaluation Checklist

• Visual aids are clearly integrated with the content of the presentation
• Photographs and illustrations suit the overall tone of the presentation
• Images and text are large and clear enough for the viewer to see or read
• Images are shown with explanatory text or a caption
• Informational graphics include clear, easy-to-read labels and headings
• Text within informational graphics is easy to read (Watch out for wordiness and crowded text or a font that is too small and hard to read.)
• Formatting choices (color, different fonts, etc.) organize information effectively
• Any text within graphics is free of errors
• Hyperlinks within slides function properly
• Display text for hyperlinks is concise and informative (Never paste a link into a slide without modifying the display text.)

Writing at Work

Office software includes many options for personalizing a presentation. For instance, you can choose or create a theme and color scheme, modify how one slide transitions to the next, or even include sound effects. With so many options, students and employees sometimes get carried away. The result can seem amateurish and detract from, rather than enhance, your presentation.

Remember, you are delivering a presentation, not producing a movie. Use the customization options to help give your presentations a consistent, polished, appearance. However, do not let these special effects detract from the substance of your slides.

Using Existing Visual Media

Depending on your topic, you may be able to find images and other graphics you can use instead of creating your own. For instance, you might use photographs from a reputable news source or informational graphics created by a government agency. If you plan to use visual aids created by others, keep the following guidelines in mind:

• Set a purpose before you begin your search. You will search more efficiently if you start with a general idea of what you are looking for—a line graph of unemployment rates for the past twelve months, for example, or a video clip of the most recent State of the Union address.
• Filter out visual aids that are not relevant. You may come across eye-catching graphics and be tempted to use them even if they are only loosely related to your topic, simply because they are attention getting. Resist the temptation. If the graphic is not clearly connected to your point, it does not belong in your presentation.
• Read carefully. In addition to reading labels, headings, and captions, read any text that accompanies the visual. Make sure you understand the visual in its original context. For informational graphics, make sure you understand exactly what information is being represented. (This may seem obvious, but it is easy to misread graphic information. Take the time to examine it carefully.)
• Evaluate sources carefully and record source information. When you look for visual media to complement your presentation, you are conducting research. Apply the same standards you used for your research paper. Choose reliable sources, such as reputable news organizations, government and nonprofit organizations, and educational institutions. Verify data in additional sources. Finally, be sure to document all source information as you proceed.

Searching Efficiently for Visual Media

You will probably find it most efficient to use the Internet to search for visual aids. Many students begin by typing keywords into a search engine to locate related images. However, this search technique is not necessarily efficient, for several reasons:

• It often pulls up hundreds or even thousands of images, which may be only loosely related to your search terms.
• It can sometimes be difficult to understand the image in its original context.
• It can be hard to find copyright information about how you may use the image.

A more efficient strategy is to identify a few sources that are likely to have what you are looking for, and then search within those sites. For instance, if you need a table showing average life expectancy in different countries, you might begin with the website of the World Health Organization. If you hope to find images related to current events, news publications are an obvious choice. The Library of Congress website includes many media related to American history, culture, and politics.

Searching this way has the following advantages:

• You will often find what you are looking for faster because you are not wasting time scrolling through many irrelevant results.
• If you have chosen your sources well, you can be reasonably certain that you are getting accurate, up-to-date information.
• Images and informational graphics produced by reputable sources are likely to be high quality—easy to read and well designed.

If you do choose to use a search engine to help you locate visual media, make sure you use it wisely. Begin with a clear idea of what you are looking for. Use the advanced search settings to narrow your search. When you locate a relevant image, do not download it immediately. Read the page or site to make sure you understand the image in context. Finally, read the site’s copyright or terms of use policy—usually found at the bottom of the home page—to make sure you may use the material.

If you are unable to find what you are looking for on the Internet consider using print sources of visual media. You may choose to mount these for display or scan them and incorporate the files into an electronic presentation. (Scanning printed pages may lower the quality of the image. However, if you are skilled at using photo-editing software, you may be able to improve the quality of the scanned image.)

Inserting Hyperlinks in an Electronic Presentation

If you are working with images, audio, or video footage available online, you may wish to insert a link within your presentation. Then, during your presentation, you can simply click the link to open the website in a separate window and toggle between windows to return to your presentation slides.

To insert a hyperlink within your presentation, click on insert in the toolbar and then select hyperlink from the menu. Doing so will open a dialogue box where you can paste your link and modify the accompanying display text shown on your slide.

Copyright and Fair Use

Before you download (or scan) any visual media, make sure you have the right to use it. Most websites state their copyright and terms of use policy on their home page. In general, you may not use other people’s visual media for any commercial purpose without contacting the copyright holder to obtain permission and pay any specified fees.

Copyright restrictions are somewhat more ambiguous when you wish to download visual media for educational uses. Some educational uses of copyrighted materials are generally considered fair use —meaning that it is legally and ethically acceptable to use the material in your work. However, do not assume that because you are using the media for an educational purpose, you are automatically in the clear. Make sure your work meets the guidelines in the following checklist. If it does, you can be reasonably confident that it would be considered fair use in a court of law and always give credit to the source.

Checklist 14.2

Media Fair Use Checklist

• You are using the media for educational purposes only.
• You will make the work available only for a short period and to a limited audience. For instance, showing a copyrighted image in a classroom presentation is acceptable. Posting a presentation with copyrighted images online is problematic. In addition, avoid any uses that would allow other people to easily access and reproduce the work.
• You have used only as much of the work as needed for your purposes. For video and audio footage, limit your use to no more than 10 percent of the media—five minutes of an hour-long television show, for example. Image use is harder to quantify, but you should avoid using many images from the same source.
• You are using the media to support your own ideas, not replace them. Your use should include some commentary or place the media in context. It should be a supporting player in your presentation—not the star of the show.
• You have obtained the material legally. Purchase the media if necessary rather than using illegally pirated material.
• Your use of the media will not affect the copyright holder or benefit you financially.

By following these guidelines, you are respecting the copyright holder’s right to control the distribution of the work and to profit from it.

In some fields, such as teaching, job applicants often submit a professional portfolio to a prospective employer. Recent college graduates may include relevant course work in their portfolios or in applications to graduate school. What should you do if your course work uses copyrighted visual media?

This use of media is acceptable according to fair use guidelines. Even though you are using the work for your personal professional advancement, it is not considered an infringement on copyright as long as you follow the additional guidelines listed in the previous checklist.

Crediting Sources

As you conduct your research, make sure you document sources as you proceed. Follow the guidelines when you download images, video, or other media from the Internet or capture media from other sources. Keep track of where you accessed the media and where you can find additional information about it. You may also provide a references page at the end of the presentation to cite not only media and images but also the information in the text of your presentation. See Chapter 13 “APA and MLA Documentation and Formatting” for more information on creating a reference page.

Write captions or other explanatory text for visual media created by others, just as you would for media you created. Doing so helps keep your audience informed. It also helps ensure that you are following fair use guidelines by presenting the media with your commentary, interpretation, or analysis. In your caption or elsewhere in your presentation, note the source of any media you did not create yourself. You do not need to provide a full bibliographical citation, but do give credit where it is due.

In this exercise, you will locate visual aids created by others and continue developing the work you began earlier. Complete these steps.

1. Revisit the ideas you developed in Note 14.24 “Exercise 1” . Choose at least two ideas for which it would make more sense to find the visual aid than to create it yourself. 2. Use the search tips provided in this section to locate at least two visual aids from reputable sources that you can use. Prepare them for your presentation by adding clarifying text as needed. Be sure to credit your source. 3. Incorporate the visual aids you created in Note 14.26 “Exercise 2” and Note 14.32 “Exercise 3” into your presentation. This may involve preparing physical copies for display or inserting graphic files into an electronic presentation.

4. Take some time now to review how you will integrate the visual and verbal components of your presentation.

• If you are working with presentation software, refine your slides. Make sure the visual approach is consistent and suits your topic. Give your text a final proofread.
• If you are not using presentation software, review the annotated outline you created in Note 14.24 “Exercise 1” . Update it as needed to reflect your current plan. Also, determine how you will physically set up your visual aids.

Key Takeaways

• Visual aids are most effective when they are chosen with the purpose and audience in mind. They serve to add emotional impact to a presentation and to organize information more clearly.
• Visual aids should always be clearly related to the presenter’s ideas. Captions, labels, and other explanatory text help make the connection clear for the audience.
• Like writing, developing the visual components of a presentation is a process. It involves generating ideas, working with them in a draft format, and then revising and editing one’s work.
• Visual aids can be divided into two broad categories—image-based media and informational graphics.
• Widely available software programs make it relatively easy to create visual aids electronically, such as photo images, charts, and graphs.
• When using visual aids created by others, it is important to apply good research skills, follow guidelines for fair use, and credit sources appropriately.

Writing for Success Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

A Guide to Effective Data Presentation

Key objectives of data presentation, charts and graphs for great visuals, storytelling with data, visuals, and text, audiences and data presentation, the main idea in data presentation, storyboarding and data presentation, additional resources, data presentation.

Tools for effective data presentation

Financial analysts are required to present their findings in a neat, clear, and straightforward manner. They spend most of their time working with spreadsheets in MS Excel, building financial models , and crunching numbers. These models and calculations can be pretty extensive and complex and may only be understood by the analyst who created them. Effective data presentation skills are critical for being a world-class financial analyst .

It is the analyst’s job to effectively communicate the output to the target audience, such as the management team or a company’s external investors. This requires focusing on the main points, facts, insights, and recommendations that will prompt the necessary action from the audience.

One challenge is making intricate and elaborate work easy to comprehend through great visuals and dashboards. For example, tables, graphs, and charts are tools that an analyst can use to their advantage to give deeper meaning to a company’s financial information. These tools organize relevant numbers that are rather dull and give life and story to them.

Here are some key objectives to think about when presenting financial analysis:

• Visual communication
• Audience and context
• Charts, graphs, and images
• Focus on important points
• Design principles
• Storytelling
• Persuasiveness

For a breakdown of these objectives, check out Excel Dashboards & Data Visualization course to help you become a world-class financial analyst.

Charts and graphs make any financial analysis readable, easy to follow, and provide great data presentation. They are often included in the financial model’s output, which is essential for the key decision-makers in a company.

The decision-makers comprise executives and managers who usually won’t have enough time to synthesize and interpret data on their own to make sound business decisions. Therefore, it is the job of the analyst to enhance the decision-making process and help guide the executives and managers to create value for the company.

When an analyst uses charts, it is necessary to be aware of what good charts and bad charts look like and how to avoid the latter when telling a story with data.

Examples of Good Charts

As for great visuals, you can quickly see what’s going on with the data presentation, saving you time for deciphering their actual meaning. More importantly, great visuals facilitate business decision-making because their goal is to provide persuasive, clear, and unambiguous numeric communication.

For reference, take a look at the example below that shows a dashboard, which includes a gauge chart for growth rates, a bar chart for the number of orders, an area chart for company revenues, and a line chart for EBITDA margins.

To learn the step-by-step process of creating these essential tools in MS Excel, watch our video course titled “ Excel Dashboard & Data Visualization .”  Aside from what is given in the example below, our course will also teach how you can use other tables and charts to make your financial analysis stand out professionally.

Learn how to build the graph above in our Dashboards Course !

Example of Poorly Crafted Charts

A bad chart, as seen below, will give the reader a difficult time to find the main takeaway of a report or presentation, because it contains too many colors, labels, and legends, and thus, will often look too busy. It also doesn’t help much if a chart, such as a pie chart, is displayed in 3D, as it skews the size and perceived value of the underlying data. A bad chart will be hard to follow and understand.

Aside from understanding the meaning of the numbers, a financial analyst must learn to combine numbers and language to craft an effective story. Relying only on data for a presentation may leave your audience finding it difficult to read, interpret, and analyze your data. You must do the work for them, and a good story will be easier to follow. It will help you arrive at the main points faster, rather than just solely presenting your report or live presentation with numbers.

The data can be in the form of revenues, expenses, profits, and cash flow. Simply adding notes, comments, and opinions to each line item will add an extra layer of insight, angle, and a new perspective to the report.

Furthermore, by combining data, visuals, and text, your audience will get a clear understanding of the current situation,  past events, and possible conclusions and recommendations that can be made for the future.

The simple diagram below shows the different categories of your audience.

  This chart is taken from our course on how to present data .

Internal Audience

An internal audience can either be the executives of the company or any employee who works in that company. For executives, the purpose of communicating a data-filled presentation is to give an update about a certain business activity such as a project or an initiative.

Another important purpose is to facilitate decision-making on managing the company’s operations, growing its core business, acquiring new markets and customers, investing in R&D, and other considerations. Knowing the relevant data and information beforehand will guide the decision-makers in making the right choices that will best position the company toward more success.

External Audience

An external audience can either be the company’s existing clients, where there are projects in progress, or new clients that the company wants to build a relationship with and win new business from. The other external audience is the general public, such as the company’s external shareholders and prospective investors of the company.

When it comes to winning new business, the analyst’s presentation will be more promotional and sales-oriented, whereas a project update will contain more specific information for the client, usually with lots of industry jargon.

Audiences for Live and Emailed Presentation

A live presentation contains more visuals and storytelling to connect more with the audience. It must be more precise and should get to the point faster and avoid long-winded speech or text because of limited time.

In contrast, an emailed presentation is expected to be read, so it will include more text. Just like a document or a book, it will include more detailed information, because its context will not be explained with a voice-over as in a live presentation.

When it comes to details, acronyms, and jargon in the presentation, these things depend on whether your audience are experts or not.

Every great presentation requires a clear “main idea”. It is the core purpose of the presentation and should be addressed clearly. Its significance should be highlighted and should cause the targeted audience to take some action on the matter.

An example of a serious and profound idea is given below.

To communicate this big idea, we have to come up with appropriate and effective visual displays to show both the good and bad things surrounding the idea. It should put emphasis and attention on the most important part, which is the critical cash balance and capital investment situation for next year. This is an important component of data presentation.

The storyboarding below is how an analyst would build the presentation based on the big idea. Once the issue or the main idea has been introduced, it will be followed by a demonstration of the positive aspects of the company’s performance, as well as the negative aspects, which are more important and will likely require more attention.

Various ideas will then be suggested to solve the negative issues. However, before choosing the best option, a comparison of the different outcomes of the suggested ideas will be performed. Finally, a recommendation will be made that centers around the optimal choice to address the imminent problem highlighted in the big idea.

This storyboard is taken from our course on how to present data .

To get to the final point (recommendation), a great deal of analysis has been performed, which includes the charts and graphs discussed earlier, to make the whole presentation easy to follow, convincing, and compelling for your audience.

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18 Best Presentation Tools for Beautiful Presentations [In 2023]

Written by: Chloe West

Looking for the best presentation tools to help you get your presentations to the next level? Powerpoint alternatives like Visme have tons of features and tools to amp up your presentation. In this guide, we will discuss how you can make the most of some of the tools like:

• Templates and themes
• Slide layouts
• Color themes

We’ve got a lot to cover, so let’s get into it.

18 Best Presentation Tools for Beautiful Presentations

Tool #1: templates and themes, tool #2: slide layouts, tool #3: fonts, tool #4: color themes, tool #5: icons, tool #6: shapes, tool #7: stock photos, tool #8: charts and graphs, tool #9: maps, tool #10: tables, tool #11: flowcharts, tool #12: icon charts, tool #13: radials, tool #14: progress bars, tool #15: animation, tool #16: transitions, tool #17: interactivity, tool #18: audio and video.

At Visme, we have two different options for users to get started with a new presentation.

The first option is presentation templates . There are over 100 editable presentation templates in Visme that range from 2 to 15 pre-designed slides for you to easily plug your content in.

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However, we also have three separate presentation themes – Modern , Simple and Creative .

Each theme has hundreds of slide layouts that you can mix and match, or pull into your presentation and customize with your own colors, fonts and content.

Regardless of if you choose a template or theme, you have full range customization options to make the presentation your own. We just give you a visually appealing starter kit to make your life easier.

If you choose between one of our presentation themes, you have hundreds of slide layouts to choose from to build out your presentation in the way that you see fit.

Whether you need a title slide, a timeline , a slide for your services or an ending contact us slide, our slide library has plenty of options for you.

When you’re in the presentation maker , click Add Slide to access the slide library. Choose one of the categories to view each of the slide layout options available.

This allows you to reuse the same theme over and over again for multiple presentations while maintaining a fresh look each time. Just choose the slide you want to edit, add it into your presentation and customize it with your own information.

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Another important tool for your presentations that you have access to in Visme is free fonts. There are over 100 fonts for users to choose from in the presentation design dashboard.

Stick to three fonts or less. Too many different font faces can make your slides appear cluttered. It’s best to incorporate one font for headers, one for body copy and a possible third for an accent font.

If you don’t find the font you want, you can also utilize Visme’s Brand Kit to upload and access your own preferred fonts. This can include your company’s brand fonts or simply a personal favorite or two.

While many of the presentation themes and templates come with an already established color scheme , absolutely nothing is set in stone. You can switch out the color of every item in your presentation to match your company or your topic.

One great presentation tool that Visme has is color themes. This allows you to change the color scheme of your entire presentation with a single click.

You can add your own brand color scheme into the Brand Kit section of your Visme dashboard so you can easily access them later. There is also a section to create your own color themes from scratch.

The color themes you create will appear at the top of the list and will switch the colors of your presentation for you without you having to pick and choose which individual elements are which color.

Using icons in your business presentation is a great way to visualize the text in your slides. You don’t want to include only text for your audience to follow along, so incorporating graphics as a visual aid is a great way to make your content more engaging.

In Visme, users have access to over 10,000 icons with four different styles to choose from.

Since you want to stick to a single icon style throughout your presentation, this gives you a way to differentiate each presentation you create while still having tons of icon options.

Access thousands of high-quality icons and graphics!

• Vector icons to spice up any Visme design or document
• Free to use , and great for print or web.
• Customize colors to fit your design needs.

Use these high-quality icons and graphics to help visualize the main points in your next presentation.

Another great way to add a few design touches to your presentation is by incorporating shapes. These can be used to emphasize photos and text by surrounding them or to create a design by themselves.

Check out the presentation slide template below. It's a great example of how using circular frames around photos can help draw attention to them.

Here's another presentation slide template that incorporates shapes into the design.

Incorporating different shapes can help to add depth to your presentation. It’s not all text, photos and icons. Instead, there’s an entire design aspect to your slides as well.

Here’s a video of how to format shapes and lines in Visme.

Visme partners with Unsplash to bring its users a massive library of free stock photos to incorporate into presentations, infographics , social media graphics and more.

While you may have your own photos of your team, business, products and services, there are still many other options for including stock photos in your presentation.

You can use the search bar to find exactly what you’re looking for in the photo library and easily drag and drop it onto your presentation slide.

If you have a preset slide with images you want to change out, click on the photo to have the option to replace it appear in the top bar.

There are many ways to use presentation images , so be sure you browse through the photo library to see what options are available for you to use in your own slides.

If you’re presenting financial data, charts and graphs are key presentation mediums . There are many different chart and graph options available, from bar charts to line graphs and pie charts to funnel charts and more.

Want to create your own charts and graphs?

• Upload an Excel file or sync with live data from Google sheets
• Choose from 16+ types of charts, from bar and line graphs to pyramid and Mekko charts
• Customize anything, from backgrounds and placement of labels to font style and color

The Graph Engine is the first option available to users when you open up the Data tab in the design dashboard, giving you 15 chart and graph options right off the bat.

You’re able to input your data manually or import an Excel or Google spreadsheet and your dynamic chart will automatically update to reflect it.

Change colors, name axes and customize the legend. All charts and graphs in Visme can also be animated to make your presentation look even more engaging and creative.

If you’re talking about demographics or sharing information that pertains to a location within your presentation, consider adding in a map to visualize the area.

Visme’s map maker allows you to insert a world map or pinpoint any location in the world, color coding areas and creating an engaging visualization for your audience.

Set a global color for your map and color code different areas based on your information. You can hide areas on the map or showcase just one specific country or continent in the world.

There are many reasons you may need to add a table to your presentation.

You can create a schedule for the event or presentation, create a pricing table or even include a table of data next to the chart that visually represents it.

It's very easy to add a table to your presentation in Visme. You can set the number of rows and columns your table has, change cell colors, customize fonts and more.

A flowchart can help you visualize business processes, chains of command and more. And Visme makes it extremely easy to customize a premade flowchart or create one entirely from scratch.

There are several slide layouts that include flowcharts you can edit to fit your content, but it’s actually quite fun to play with the shapes and lines to create your own flow.

The flowchart elements are fully customizable so that you can choose outlines or filled in shapes, corners or rounded edges in your lines, line width and more.

An icon chart or an array is a way to represent data with icons. You can use this to differentiate between the number of men and women, cats and dogs, etc., that fall under different categories.

While the array visualization automatically comes with two icons, you can add more, change colors, switch the icons with any options from our library and more.

A radial, or circular counter, is a more engaging way to represent numbers or percentages than having them stand alone on the slide.

The thing is, not many PowerPoint alternatives have this tool. However, there are many different styles to choose from in Visme's data widget sidebar.

You’re able to customize the colors, the number, the maximum and minimum values and even whether you’re visualizing a percentage or just a number.

You can even add icons to the center of your radial to better visualize what each percentage is referencing.

Want to let your audience know how much time there is left in the presentation? Add a progress bar to the bottom of each slide.

You can also use this to show how far along the company is with creating products or gathering funding.

In Visme, you can choose from many different styles of progress bars, creating a new look and feel in each presentation you add this feature to.

To make your presentation more engaging , consider adding animation to the elements in your slides. This makes them move on the screen and helps grab the attention of your audience.

In Visme, you have six animation options:

• Fly from left
• Fly from right
• Fly from top
• Fٖٖٖly from bottom

Just remember that you only want to stick to one animation type per presentation. Having elements fly in from all different directions is not a good look and can easily overwhelm your audience.

Create beautiful and animated presentations!

• Add your own text, images, colors and more
• Add interactive buttons, transitions and animations
• Customize anything to fit your design and content needs

Watch this video to learn how you can animate text, video, shapes and images in Visme.

Your transition is the way your slides appear and disappear, and it’s a great idea to give this a bit more flair than your typical slide interchange.

With Visme, you can create transitions that not only move your slide, but each of the elements simultaneously. Simply click on the gear at the right corner of the slides to access the transitions.

The Staggered Fade, Enter from Side, Enter from Bottom, Enter from Top and Zoom In transitions all include both slide and element transitions. However, if you want to animate your elements separately, you can choose the transition Simple Fade or Slide In.

Visme also offers several great ways to make your presentation interactive.

Have Q&As, bring props, have your audience raise their hands and more. You create hyperlinks between slides and even design elements to create a unique experience for your audience.

This is a great way to make your presentation stand out and get your audience involved, so be sure to keep some of these interactivity ideas in mind.

Adding an audio narrative, recording a voice-over for your slides, incorporating background music or even embedding a video can be a great way to increase engagement in your presentation.

You can record audio directly in Visme, embed video links or embed any other type of online content directly in your presentation slides.

This can also give you a break from presenting during longer sessions, breaking up the monotony of your audience listening to the same thing for the duration of the time.

Watch the video below to learn how to embed video into your presentation and capture your audience's attention.

Looking for the Best Presentation Software to Use These Tools?

There you have it. We’ve shared 18 valuable tools for beautifying your next presentation.

But here’s a caveat! When preparing your presentation, don’t throw in all of these tools. Match the presentation topic with the tool that will have the most impact on your audience.

While there is a lot of presentation software out there—like PowerPoint, Keynote, Beautiful.ai, Prezi, Canva, Visme and more—what tools do you use for your presentation? Visme comes preloaded with all of the best presentation tools we’ve mentioned and more. Use them to create a presentation that your potential customers and investors will fall in love with.

Sign up for a free Visme account today to get started, and check out all of our presentation templates to find something you love.

Create beautiful presentations faster with Visme.

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About the Author

Chloe West is the content marketing manager at Visme. Her experience in digital marketing includes everything from social media, blogging, email marketing to graphic design, strategy creation and implementation, and more. During her spare time, she enjoys exploring her home city of Charleston with her son.

Data Presentation: Use of Tables and Graphics

• First Online: 08 June 2022

Cite this chapter

• Anand J. Thakur 2  

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In an era of evidence based medicine, data is an important factor and needs to be presented in a way that is quickly understood by the audience. People are generally weak at understanding data. Visualization makes it easier for the audience to grasp and recall data. It should be presented in an attractive style to create interest in audience’s mind; Data may be presented as a table or graphic. There are 3 types of tables: Formal (numbers), textural, and matrix; each one has its peculiarities and usefulness. Rules for construction of these table are described. There are several graphics to present data and one that is most suitable for the variables under consideration is chosen. Numerical (quantitative) data is presented in a bar chart, pictogram, pie chart, or choropleth map. Descriptive, categorical, and frequency data (qualitative) are presented in histogram, frequency polygon, frequency curve, line chart, and scatter diagram. Decision trees and genealogical charts are used in special circumstances. Example of each of these graphics is discussed with its usefulness and shortcomings. Recommendations on use of tables and graphics for a specific data are made for expediency and usability.

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Anand J. Thakur

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Thakur, A.J. (2022). Data Presentation: Use of Tables and Graphics. In: Tapping the Power of PowerPoint for Medical Posters and Presentations. Springer, Singapore. https://doi.org/10.1007/978-981-19-1816-2_8

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Olympic opening ceremony drag performance resembling Last Supper rankles conservatives

PARIS — The extravagant opening ceremony of the 2024 Paris Olympics has caused fury among the populist and religious right in the United States and elsewhere, with critics especially unhappy about an apparent depiction of the Last Supper featuring drag performers.

A fashion show at the ceremony included a scene that resembled a modern re-creation of Leonardo da Vinci’s famous painting, French actor and singer Philippe Katerine appeared as the Greek god Dionysus, painted blue and wearing little more than a bunch of flowers covering his modesty.

While some fans loved this unabashed display of French camp and kitsch, others — particularly those who espouse conservative or Christian beliefs — were not happy with it.

Follow along for live coverage

“In this scene from the Olympic opening ceremony, the famous painting of The Last Supper is recreated, but Jesus is replaced with an obese woman, while queer and trans figures (including a child!) depict her apostles,” Jenna Ellis, former 2020 campaign attorney to Donald Trump, told her 1 million followers on X.

She described the ceremony as containing “overt pagan and satanic symbolism.”

Stream every moment and every medal of the 2024 Paris Olympics on Peacock .

The Last Supper refers to the final meal that Jesus Christ shared with his 12 apostles before he was crucified. It’s also a popular subject in Christian art, most famously depicted by da Vinci, who painted a scene that captured the apostles’ reaction to Jesus’ announcement of his betrayal.

Thomas Jolly, the artistic director of the opening ceremony, defended the production when asked at a news conference Saturday about some of the backlash. Jolly said he was unaware of the criticism and wanted to display “inclusion.”

“When we want to include everyone and not exclude anyone, questions are raised,” he said at an International Olympic Committee media briefing.

“Our subject was not to be subversive. We never wanted to be subversive. We wanted to talk about diversity. Diversity means being together,” he continued. “We wanted to include everyone, as simple as that. In France, we have freedom of creation, artistic freedom. We are lucky in France to live in a free country. I didn’t have any specific messages that I wanted to deliver. In France, we are republic, we have the right to love whom we want, we have the right not to be worshippers, we have a lot of rights in France, and this is what I wanted to convey.”

Kansas City Chiefs kicker Harrison Butker called the depiction “crazy” in a post on Instagram and quoted the New Testament book Epistle to the Galatians, warning that “for what things a man shall sow, those also shall he reap.” Butker sparked accusations of sexism and homophobia over a commencement speech in May in which he told a class of college graduates that one of the “most important” titles a woman can hold is homemaker.

Bishop Emmanuel Gobillard, a spokesperson representing the Holy See for the 2024 Paris Olympics, told NBC News that the depiction of the Last Supper left him “deeply hurt.”

“The fact that our religion should be mocked is usual and we are used to blasphemy in France, but the context isn’t the same,” he said. “In an event that brings together all or part of the population, I found this staging hurtful and out of place.”

Far-right French politician Marion Marechal-Le Pen said in a post on X that the performance was “not France that is speaking but a left-wing minority ready for any provocation.”

Elon Musk responded to and amplified several memes decrying the “wokeness” of the event. And Kyle Becker, a former Fox News producer with more than half a million X followers, said the Games had “gone full Woke dystopian.”

This ignited debates, held in varying levels of good faith, on social media.

The British writer and broadcaster David Aaronovitch was among those to point out that the Last Supper has been “pastiched, parodied and altered tens of thousands of times” since da Vinci painted it in the 1490s.

Nonetheless, Bishop Robert Barron, of the Diocese of Winona-Rochester, in Minnesota, asked his 280,000 X followers: “Would they ever have dreamed of mocking in this gross, public way, a scene from the quran?” He responded that “we all know the answer.”

French freedom of expression has not been aimed solely at one religion, however. In 2015, gunmen killed 12 people to avenge controversial cartoons of the Prophet Muhammad in an attack on the French satirical newspaper Charlie Hebdo. The publication even republished the controversial caricatures five years later to mark the start of the attackers’ trial.

This “deeply secular postmodern society knows who its enemy is, they are naming it, and we should believe them,” Barron said in a video message. “We Christians, we Catholics should not be sheepish. We should resist. We should make our voices heard.”

Alexander Smith reported from Paris and Minyvonne Burke reported from Pittsburgh

Alexander Smith is a senior reporter for NBC News Digital based in London.

Minyvonne Burke is a senior breaking news reporter for NBC News.

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Statistical data presentation

1 Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Korea.

Sangseok Lee

2 Department of Anesthesiology and Pain Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea.

Data are usually collected in a raw format and thus the inherent information is difficult to understand. Therefore, raw data need to be summarized, processed, and analyzed. However, no matter how well manipulated, the information derived from the raw data should be presented in an effective format, otherwise, it would be a great loss for both authors and readers. In this article, the techniques of data and information presentation in textual, tabular, and graphical forms are introduced. Text is the principal method for explaining findings, outlining trends, and providing contextual information. A table is best suited for representing individual information and represents both quantitative and qualitative information. A graph is a very effective visual tool as it displays data at a glance, facilitates comparison, and can reveal trends and relationships within the data such as changes over time, frequency distribution, and correlation or relative share of a whole. Text, tables, and graphs for data and information presentation are very powerful communication tools. They can make an article easy to understand, attract and sustain the interest of readers, and efficiently present large amounts of complex information. Moreover, as journal editors and reviewers glance at these presentations before reading the whole article, their importance cannot be ignored.

Introduction

Data are a set of facts, and provide a partial picture of reality. Whether data are being collected with a certain purpose or collected data are being utilized, questions regarding what information the data are conveying, how the data can be used, and what must be done to include more useful information must constantly be kept in mind.

Since most data are available to researchers in a raw format, they must be summarized, organized, and analyzed to usefully derive information from them. Furthermore, each data set needs to be presented in a certain way depending on what it is used for. Planning how the data will be presented is essential before appropriately processing raw data.

First, a question for which an answer is desired must be clearly defined. The more detailed the question is, the more detailed and clearer the results are. A broad question results in vague answers and results that are hard to interpret. In other words, a well-defined question is crucial for the data to be well-understood later. Once a detailed question is ready, the raw data must be prepared before processing. These days, data are often summarized, organized, and analyzed with statistical packages or graphics software. Data must be prepared in such a way they are properly recognized by the program being used. The present study does not discuss this data preparation process, which involves creating a data frame, creating/changing rows and columns, changing the level of a factor, categorical variable, coding, dummy variables, variable transformation, data transformation, missing value, outlier treatment, and noise removal.

We describe the roles and appropriate use of text, tables, and graphs (graphs, plots, or charts), all of which are commonly used in reports, articles, posters, and presentations. Furthermore, we discuss the issues that must be addressed when presenting various kinds of information, and effective methods of presenting data, which are the end products of research, and of emphasizing specific information.

Data Presentation

Data can be presented in one of the three ways:

–as text;

–in tabular form; or

–in graphical form.

Methods of presentation must be determined according to the data format, the method of analysis to be used, and the information to be emphasized. Inappropriately presented data fail to clearly convey information to readers and reviewers. Even when the same information is being conveyed, different methods of presentation must be employed depending on what specific information is going to be emphasized. A method of presentation must be chosen after carefully weighing the advantages and disadvantages of different methods of presentation. For easy comparison of different methods of presentation, let us look at a table ( Table 1 ) and a line graph ( Fig. 1 ) that present the same information [ 1 ]. If one wishes to compare or introduce two values at a certain time point, it is appropriate to use text or the written language. However, a table is the most appropriate when all information requires equal attention, and it allows readers to selectively look at information of their own interest. Graphs allow readers to understand the overall trend in data, and intuitively understand the comparison results between two groups. One thing to always bear in mind regardless of what method is used, however, is the simplicity of presentation.

Values are expressed as mean ± SD. Group C: normal saline, Group D: dexmedetomidine. SBP: systolic blood pressure, DBP: diastolic blood pressure, MBP: mean blood pressure, HR: heart rate. * P < 0.05 indicates a significant increase in each group, compared with the baseline values. † P < 0.05 indicates a significant decrease noted in Group D, compared with the baseline values. ‡ P < 0.05 indicates a significant difference between the groups.

Text presentation

Text is the main method of conveying information as it is used to explain results and trends, and provide contextual information. Data are fundamentally presented in paragraphs or sentences. Text can be used to provide interpretation or emphasize certain data. If quantitative information to be conveyed consists of one or two numbers, it is more appropriate to use written language than tables or graphs. For instance, information about the incidence rates of delirium following anesthesia in 2016–2017 can be presented with the use of a few numbers: “The incidence rate of delirium following anesthesia was 11% in 2016 and 15% in 2017; no significant difference of incidence rates was found between the two years.” If this information were to be presented in a graph or a table, it would occupy an unnecessarily large space on the page, without enhancing the readers' understanding of the data. If more data are to be presented, or other information such as that regarding data trends are to be conveyed, a table or a graph would be more appropriate. By nature, data take longer to read when presented as texts and when the main text includes a long list of information, readers and reviewers may have difficulties in understanding the information.

Table presentation

Tables, which convey information that has been converted into words or numbers in rows and columns, have been used for nearly 2,000 years. Anyone with a sufficient level of literacy can easily understand the information presented in a table. Tables are the most appropriate for presenting individual information, and can present both quantitative and qualitative information. Examples of qualitative information are the level of sedation [ 2 ], statistical methods/functions [ 3 , 4 ], and intubation conditions [ 5 ].

The strength of tables is that they can accurately present information that cannot be presented with a graph. A number such as “132.145852” can be accurately expressed in a table. Another strength is that information with different units can be presented together. For instance, blood pressure, heart rate, number of drugs administered, and anesthesia time can be presented together in one table. Finally, tables are useful for summarizing and comparing quantitative information of different variables. However, the interpretation of information takes longer in tables than in graphs, and tables are not appropriate for studying data trends. Furthermore, since all data are of equal importance in a table, it is not easy to identify and selectively choose the information required.

For a general guideline for creating tables, refer to the journal submission requirements 1) .

Heat maps for better visualization of information than tables

Heat maps help to further visualize the information presented in a table by applying colors to the background of cells. By adjusting the colors or color saturation, information is conveyed in a more visible manner, and readers can quickly identify the information of interest ( Table 2 ). Software such as Excel (in Microsoft Office, Microsoft, WA, USA) have features that enable easy creation of heat maps through the options available on the “conditional formatting” menu.

All numbers were created by the author. SBP: systolic blood pressure, DBP: diastolic blood pressure, MBP: mean blood pressure, HR: heart rate.

Graph presentation

Whereas tables can be used for presenting all the information, graphs simplify complex information by using images and emphasizing data patterns or trends, and are useful for summarizing, explaining, or exploring quantitative data. While graphs are effective for presenting large amounts of data, they can be used in place of tables to present small sets of data. A graph format that best presents information must be chosen so that readers and reviewers can easily understand the information. In the following, we describe frequently used graph formats and the types of data that are appropriately presented with each format with examples.

Scatter plot

Scatter plots present data on the x - and y -axes and are used to investigate an association between two variables. A point represents each individual or object, and an association between two variables can be studied by analyzing patterns across multiple points. A regression line is added to a graph to determine whether the association between two variables can be explained or not. Fig. 2 illustrates correlations between pain scoring systems that are currently used (PSQ, Pain Sensitivity Questionnaire; PASS, Pain Anxiety Symptoms Scale; PCS, Pain Catastrophizing Scale) and Geop-Pain Questionnaire (GPQ) with the correlation coefficient, R, and regression line indicated on the scatter plot [ 6 ]. If multiple points exist at an identical location as in this example ( Fig. 2 ), the correlation level may not be clear. In this case, a correlation coefficient or regression line can be added to further elucidate the correlation.

Bar graph and histogram

A bar graph is used to indicate and compare values in a discrete category or group, and the frequency or other measurement parameters (i.e. mean). Depending on the number of categories, and the size or complexity of each category, bars may be created vertically or horizontally. The height (or length) of a bar represents the amount of information in a category. Bar graphs are flexible, and can be used in a grouped or subdivided bar format in cases of two or more data sets in each category. Fig. 3 is a representative example of a vertical bar graph, with the x -axis representing the length of recovery room stay and drug-treated group, and the y -axis representing the visual analog scale (VAS) score. The mean and standard deviation of the VAS scores are expressed as whiskers on the bars ( Fig. 3 ) [ 7 ].

By comparing the endpoints of bars, one can identify the largest and the smallest categories, and understand gradual differences between each category. It is advised to start the x - and y -axes from 0. Illustration of comparison results in the x - and y -axes that do not start from 0 can deceive readers' eyes and lead to overrepresentation of the results.

One form of vertical bar graph is the stacked vertical bar graph. A stack vertical bar graph is used to compare the sum of each category, and analyze parts of a category. While stacked vertical bar graphs are excellent from the aspect of visualization, they do not have a reference line, making comparison of parts of various categories challenging ( Fig. 4 ) [ 8 ].

A pie chart, which is used to represent nominal data (in other words, data classified in different categories), visually represents a distribution of categories. It is generally the most appropriate format for representing information grouped into a small number of categories. It is also used for data that have no other way of being represented aside from a table (i.e. frequency table). Fig. 5 illustrates the distribution of regular waste from operation rooms by their weight [ 8 ]. A pie chart is also commonly used to illustrate the number of votes each candidate won in an election.

Line plot with whiskers

A line plot is useful for representing time-series data such as monthly precipitation and yearly unemployment rates; in other words, it is used to study variables that are observed over time. Line graphs are especially useful for studying patterns and trends across data that include climatic influence, large changes or turning points, and are also appropriate for representing not only time-series data, but also data measured over the progression of a continuous variable such as distance. As can be seen in Fig. 1 , mean and standard deviation of systolic blood pressure are indicated for each time point, which enables readers to easily understand changes of systolic pressure over time [ 1 ]. If data are collected at a regular interval, values in between the measurements can be estimated. In a line graph, the x-axis represents the continuous variable, while the y-axis represents the scale and measurement values. It is also useful to represent multiple data sets on a single line graph to compare and analyze patterns across different data sets.

Box and whisker chart

A box and whisker chart does not make any assumptions about the underlying statistical distribution, and represents variations in samples of a population; therefore, it is appropriate for representing nonparametric data. AA box and whisker chart consists of boxes that represent interquartile range (one to three), the median and the mean of the data, and whiskers presented as lines outside of the boxes. Whiskers can be used to present the largest and smallest values in a set of data or only a part of the data (i.e. 95% of all the data). Data that are excluded from the data set are presented as individual points and are called outliers. The spacing at both ends of the box indicates dispersion in the data. The relative location of the median demonstrated within the box indicates skewness ( Fig. 6 ). The box and whisker chart provided as an example represents calculated volumes of an anesthetic, desflurane, consumed over the course of the observation period ( Fig. 7 ) [ 9 ].

Three-dimensional effects

Most of the recently introduced statistical packages and graphics software have the three-dimensional (3D) effect feature. The 3D effects can add depth and perspective to a graph. However, since they may make reading and interpreting data more difficult, they must only be used after careful consideration. The application of 3D effects on a pie chart makes distinguishing the size of each slice difficult. Even if slices are of similar sizes, slices farther from the front of the pie chart may appear smaller than the slices closer to the front ( Fig. 8 ).

Drawing a graph: example

Finally, we explain how to create a graph by using a line graph as an example ( Fig. 9 ). In Fig. 9 , the mean values of arterial pressure were randomly produced and assumed to have been measured on an hourly basis. In many graphs, the x- and y-axes meet at the zero point ( Fig. 9A ). In this case, information regarding the mean and standard deviation of mean arterial pressure measurements corresponding to t = 0 cannot be conveyed as the values overlap with the y-axis. The data can be clearly exposed by separating the zero point ( Fig. 9B ). In Fig. 9B , the mean and standard deviation of different groups overlap and cannot be clearly distinguished from each other. Separating the data sets and presenting standard deviations in a single direction prevents overlapping and, therefore, reduces the visual inconvenience. Doing so also reduces the excessive number of ticks on the y-axis, increasing the legibility of the graph ( Fig. 9C ). In the last graph, different shapes were used for the lines connecting different time points to further allow the data to be distinguished, and the y-axis was shortened to get rid of the unnecessary empty space present in the previous graphs ( Fig. 9D ). A graph can be made easier to interpret by assigning each group to a different color, changing the shape of a point, or including graphs of different formats [ 10 ]. The use of random settings for the scale in a graph may lead to inappropriate presentation or presentation of data that can deceive readers' eyes ( Fig. 10 ).

Owing to the lack of space, we could not discuss all types of graphs, but have focused on describing graphs that are frequently used in scholarly articles. We have summarized the commonly used types of graphs according to the method of data analysis in Table 3 . For general guidelines on graph designs, please refer to the journal submission requirements 2) .

Conclusions

Text, tables, and graphs are effective communication media that present and convey data and information. They aid readers in understanding the content of research, sustain their interest, and effectively present large quantities of complex information. As journal editors and reviewers will scan through these presentations before reading the entire text, their importance cannot be disregarded. For this reason, authors must pay as close attention to selecting appropriate methods of data presentation as when they were collecting data of good quality and analyzing them. In addition, having a well-established understanding of different methods of data presentation and their appropriate use will enable one to develop the ability to recognize and interpret inappropriately presented data or data presented in such a way that it deceives readers' eyes [ 11 ].

<Appendix>

Output for presentation.

Discovery and communication are the two objectives of data visualization. In the discovery phase, various types of graphs must be tried to understand the rough and overall information the data are conveying. The communication phase is focused on presenting the discovered information in a summarized form. During this phase, it is necessary to polish images including graphs, pictures, and videos, and consider the fact that the images may look different when printed than how appear on a computer screen. In this appendix, we discuss important concepts that one must be familiar with to print graphs appropriately.

The KJA asks that pictures and images meet the following requirement before submission 3)

“Figures and photographs should be submitted as ‘TIFF’ files. Submit files of figures and photographs separately from the text of the paper. Width of figure should be 84 mm (one column). Contrast of photos or graphs should be at least 600 dpi. Contrast of line drawings should be at least 1,200 dpi. The Powerpoint file (ppt, pptx) is also acceptable.”

Unfortunately, without sufficient knowledge of computer graphics, it is not easy to understand the submission requirement above. Therefore, it is necessary to develop an understanding of image resolution, image format (bitmap and vector images), and the corresponding file specifications.

Resolution is often mentioned to describe the quality of images containing graphs or CT/MRI scans, and video files. The higher the resolution, the clearer and closer to reality the image is, while the opposite is true for low resolutions. The most representative unit used to describe a resolution is “dpi” (dots per inch): this literally translates to the number of dots required to constitute 1 inch. The greater the number of dots, the higher the resolution. The KJA submission requirements recommend 600 dpi for images, and 1,200 dpi 4) for graphs. In other words, resolutions in which 600 or 1,200 dots constitute one inch are required for submission.

There are requirements for the horizontal length of an image in addition to the resolution requirements. While there are no requirements for the vertical length of an image, it must not exceed the vertical length of a page. The width of a column on one side of a printed page is 84 mm, or 3.3 inches (84/25.4 mm ≒ 3.3 inches). Therefore, a graph must have a resolution in which 1,200 dots constitute 1 inch, and have a width of 3.3 inches.

Bitmap and Vector

Methods of image construction are important. Bitmap images can be considered as images drawn on section paper. Enlarging the image will enlarge the picture along with the grid, resulting in a lower resolution; in other words, aliasing occurs. On the other hand, reducing the size of the image will reduce the size of the picture, while increasing the resolution. In other words, resolution and the size of an image are inversely proportionate to one another in bitmap images, and it is a drawback of bitmap images that resolution must be considered when adjusting the size of an image. To enlarge an image while maintaining the same resolution, the size and resolution of the image must be determined before saving the image. An image that has already been created cannot avoid changes to its resolution according to changes in size. Enlarging an image while maintaining the same resolution will increase the number of horizontal and vertical dots, ultimately increasing the number of pixels 5) of the image, and the file size. In other words, the file size of a bitmap image is affected by the size and resolution of the image (file extensions include JPG [JPEG] 6) , PNG 7) , GIF 8) , and TIF [TIFF] 9) . To avoid this complexity, the width of an image can be set to 4 inches and its resolution to 900 dpi to satisfy the submission requirements of most journals [ 12 ].

Vector images overcome the shortcomings of bitmap images. Vector images are created based on mathematical operations of line segments and areas between different points, and are not affected by aliasing or pixelation. Furthermore, they result in a smaller file size that is not affected by the size of the image. They are commonly used for drawings and illustrations (file extensions include EPS 10) , CGM 11) , and SVG 12) ).

Finally, the PDF 13) is a file format developed by Adobe Systems (Adobe Systems, CA, USA) for electronic documents, and can contain general documents, text, drawings, images, and fonts. They can also contain bitmap and vector images. While vector images are used by researchers when working in Powerpoint, they are saved as 960 × 720 dots when saved in TIFF format in Powerpoint. This results in a resolution that is inappropriate for printing on a paper medium. To save high-resolution bitmap images, the image must be saved as a PDF file instead of a TIFF, and the saved PDF file must be imported into an imaging processing program such as Photoshop™(Adobe Systems, CA, USA) to be saved in TIFF format [ 12 ].

1) Instructions to authors in KJA; section 5-(9) Table; https://ekja.org/index.php?body=instruction

2) Instructions to Authors in KJA; section 6-1)-(10) Figures and illustrations in Manuscript preparation; https://ekja.org/index.php?body=instruction

3) Instructions to Authors in KJA; section 6-1)-(10) Figures and illustrations in Manuscript preparation; https://ekja.org/index.php?body=instruction

4) Resolution; in KJA, it is represented by “contrast.”

5) Pixel is a minimum unit of an image and contains information of a dot and color. It is derived by multiplying the number of vertical and horizontal dots regardless of image size. For example, Full High Definition (FHD) monitor has 1920 × 1080 dots ≒ 2.07 million pixel.

6) Joint Photographic Experts Group.

7) Portable Network Graphics.

8) Graphics Interchange Format

9) Tagged Image File Format; TIFF

10) Encapsulated PostScript.

11) Computer Graphics Metafile.

12) Scalable Vector Graphics.

13) Portable Document Format.

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FACT SHEET: Biden- ⁠ Harris Administration Announces New AI Actions and Receives Additional Major Voluntary Commitment on   AI

Nine months ago, President Biden issued a landmark Executive Order to ensure that America leads the way in seizing the promise and managing the risks of artificial intelligence (AI). This Executive Order built on the voluntary commitments he and Vice President Harris received from 15 leading U.S. AI companies last year. Today, the administration announced that Apple has signed onto the voluntary commitments, further cementing these commitments as cornerstones of responsible AI innovation. In addition, federal agencies reported that they completed all of the 270-day actions in the Executive Order on schedule, following their on-time completion of every other task required to date . Agencies also progressed on other work directed for longer timeframes. Following the Executive Order and a series of calls to action made by Vice President Harris as part of her major policy speech before the Global Summit on AI Safety, agencies all across government have acted boldly. They have taken steps to mitigate AI’s safety and security risks, protect Americans’ privacy, advance equity and civil rights, stand up for consumers and workers, promote innovation and competition, advance American leadership around the world, and more. Actions that agencies reported today as complete include the following: Managing Risks to Safety and Security: Over 270 days, the Executive Order directed agencies to take sweeping action to address AI’s safety and security risks, including by releasing vital safety guidance and building capacity to test and evaluate AI. To protect safety and security, agencies have:

• Released for public comment new technical guidelines from the AI Safety Institute (AISI) for leading AI developers in managing the evaluation of misuse of dual-use foundation models. AISI’s guidelines detail how leading AI developers can help prevent increasingly capable AI systems from being misused to harm individuals, public safety, and national security, as well as how developers can increase transparency about their products.
• Published final frameworks on managing generative AI risks and securely developing generative AI systems and dual-use foundation models. These documents by the National Institute of Standards and Technology (NIST) will provide additional guidance that builds on NIST’s AI Risk Management Framework, which offered individuals, organizations, and society a framework to manage AI risks and has been widely adopted both in the U.S. and globally. NIST also submitted a report to the White House outlining tools and techniques to reduce the risks from synthetic content.
• Developed and expanded AI testbeds and model evaluation tools at the Department of Energy (DOE). DOE, in coordination with interagency partners, is using its testbeds to evaluate AI model safety and security, especially for risks that AI models might pose to critical infrastructure, energy security, and national security. DOE’s testbeds are also being used to explore novel AI hardware and software systems, including privacy-enhancing technologies that improve AI trustworthiness. The National Science Foundation (NSF) also launched an initiative to help fund researchers outside the federal government design and plan AI-ready testbeds.
• Reported results of piloting AI to protect vital government software.  The Department of Defense (DoD) and Department of Homeland Security (DHS) reported findings from their AI pilots to address vulnerabilities in government networks used, respectively, for national security purposes and for civilian government. These steps build on previous work to advance such pilots within 180 days of the Executive Order.
• Issued a call to action from the Gender Policy Council and Office of Science and Technology Policy to combat image-based sexual abuse, including synthetic content generated by AI. Image-based sexual abuse has emerged as one of the fastest growing harmful uses of AI to-date, and the call to action invites technology companies and other industry stakeholders to curb it. This call flowed from Vice President Harris’s remarks in London before the AI Safety Summit, which underscored that deepfake image-based sexual abuse is an urgent threat that demands global action.

Bringing AI Talent into Government Last year, the Executive Order launched a government-wide AI Talent Surge that is bringing hundreds of AI and AI-enabling professionals into government. Hired individuals are working on critical AI missions, such as informing efforts to use AI for permitting, advising on AI investments across the federal government, and writing policy for the use of AI in government.

• To increase AI capacity across the federal government for both national security and non-national security missions, the AI Talent Surge has made over 200 hires to-date, including through the Presidential Innovation Fellows AI cohort and the DHS AI Corps .
• Building on the AI Talent Surge 6-month report , the White House Office of Science and Technology Policy announced new commitments from across the technology ecosystem, including nearly $100 million in funding, to bolster the broader public interest technology ecosystem and build infrastructure for bringing technologists into government service.

Advancing Responsible AI Innovation President Biden’s Executive Order directed further actions to seize AI’s promise and deepen the U.S. lead in AI innovation while ensuring AI’s responsible development and use across our economy and society. Within 270 days, agencies have:

• Prepared and will soon release a report on the potential benefits, risks, and implications of dual-use foundation models for which the model weights are widely available, including related policy recommendations. The Department of Commerce’s report draws on extensive outreach to experts and stakeholders, including hundreds of public comments submitted on this topic.
• Awarded over 80 research teams’ access to computational and other AI resources through the National AI Research Resource (NAIRR) pilot —a national infrastructure led by NSF, in partnership with DOE, NIH, and other governmental and nongovernmental partners, that makes available resources to support the nation’s AI research and education community. Supported projects will tackle deepfake detection, advance AI safety, enable next-generation medical diagnoses and further other critical AI priorities.
• Released a guide for designing safe, secure, and trustworthy AI tools for use in education. The Department of Education’s guide discusses how developers of educational technologies can design AI that benefits students and teachers while advancing equity, civil rights, trust, and transparency. This work builds on the Department’s 2023 report outlining recommendations for the use of AI in teaching and learning.
• Published guidance on evaluating the eligibility of patent claims involving inventions related to AI technology,  as well as other emerging technologies. The guidance by the U.S. Patent and Trademark Office will guide those inventing in the AI space to protect their AI inventions and assist patent examiners reviewing applications for patents on AI inventions.
• Issued a report on federal research and development (R&D) to advance trustworthy AI over the past four years. The report by the National Science and Technology Council examines an annual federal AI R&D budget of nearly $3 billion.
• Launched a $23 million initiative to promote the use of privacy-enhancing technologies to solve real-world problems, including related to AI.  Working with industry and agency partners, NSF will invest through its new Privacy-preserving Data Sharing in Practice program in efforts to apply, mature, and scale privacy-enhancing technologies for specific use cases and establish testbeds to accelerate their adoption.
• Announced millions of dollars in further investments to advance responsible AI development and use throughout our society. These include $30 million invested through NSF’s Experiential Learning in Emerging and Novel Technologies program—which supports inclusive experiential learning in fields like AI—and $10 million through NSF’s ExpandAI program, which helps build capacity in AI research at minority-serving institutions while fostering the development of a diverse, AI-ready workforce.

Advancing U.S. Leadership Abroad President Biden’s Executive Order emphasized that the United States lead global efforts to unlock AI’s potential and meet its challenges. To advance U.S. leadership on AI, agencies have:

• Issued a comprehensive plan for U.S. engagement on global AI standards.  The plan, developed by the NIST, incorporates broad public and private-sector input, identifies objectives and priority areas for AI standards work, and lays out actions for U.S. stakeholders including U.S. agencies. NIST and others agencies will report on priority actions in 180 days. 
• Developed guidance for managing risks to human rights posed by AI. The Department of State’s “Risk Management Profile for AI and Human Rights”—developed in close coordination with NIST and the U.S. Agency for International Development—recommends actions based on the NIST AI Risk Management Framework to governments, the private sector, and civil society worldwide, to identify and manage risks to human rights arising from the design, development, deployment, and use of AI. 
• Launched a global network of AI Safety Institutes and other government-backed scientific offices to advance AI safety at a technical level. This network will accelerate critical information exchange and drive toward common or compatible safety evaluations and policies.
• Launched a landmark United Nations General Assembly resolution . The unanimously adopted resolution, with more than 100 co-sponsors, lays out a common vision for countries around the world to promote the safe and secure use of AI to address global challenges.
• Expanded global support for the U.S.-led Political Declaration on the Responsible Military Use of Artificial Intelligence and Autonomy.   Fifty-five nations now endorse the political declaration, which outlines a set of norms for the responsible development, deployment, and use of military AI capabilities.

The Table below summarizes many of the activities that federal agencies have completed in response to the Executive Order:

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