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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.

If you need a quick method to create a data presentation, check out our  AI presentation maker . A tool in which you add the topic, curate the outline, select a design, and let AI do the work for you.

[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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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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10 Ultimate Data Visualization Techniques to Make your PowerPoint Presentation Stand Out!

Getting audience attention towards your PowerPoint presentation is a feat in and of itself.

To achieve this feat possibly you have spent hours crafting a winning PPT to get that attention.

Perhaps many of you likely have spent hundreds of bucks too.

But despite all efforts, you still struggle to get that desired applause from viewers. You have done all that was required to make a PPT standalone. So, the million dollar question is what went wrong?

Rest easy! We have figured out the culprit.

Well, we all know that figures or data are imperative to make an impact. The problem is that with each passing day data or figures are becoming bigger and bigger. Managing and presenting huge data or figures in an engaging manner especially the big ones is a challenge in itself.

That’s exactly the weak link where every second presenter fails to hit the captivating chord.

Even skipping data or figures calculatedly is not going to serve the purpose. In fact, such a strategy may backfire and perhaps will do more harm than benefit. 

All you need to do is to understand the science of Data Visualization. Data visualization means the depiction of information in the form of visuals, chart and diagrams.

Well, we know many of you must be already applying charts, bar graphs and pie charts etc. to represent data. Frankly speaking, nowadays every second presenter is using such old data visualization tricks. These are good enough. But to create a jaw-dropping effect now you need to master new data visualization tricks. 

To help you out, here are 10 data visualization techniques or tricks to make your PowerPoint stand out.

Data Visualization Techniques for PowerPoint Presentations

1. Speedometer Dashboard

An automobile dashboard provides information about various parameters of vehicles. In the business world, it can be applied as a metaphor of Key Performance Indicator (KPI). To put in other words, a dashboard helps to visualize figures related to sales, production, efficiency, planning, client satisfaction level or key market trends.    

Download Speedometer PowerPoint Template

2. Batteries

A metaphor of battery may seem simple, but it has the potential to boost audience engagement. Presenters can apply battery visuals to symbolically represent figures related to employee satisfaction surveys, energy, motivation level of employees, strength, resources, time and financial state. Best is, instead of using traditional pie charts metaphors of batteries look trendy and are easy to comprehend. 

Download Batteries PowerPoint Template

3. Cylinders

Like batteries, the metaphor of cylinders perfectly fits to symbolize figures related to targets and goals. In short, different levels of cylinders can be applied in a presentation slide to depict various business figures.

Download Cylinders PowerPoint Template

4. Thermometer

Thermometer is a perfect symbol to portray figures related to sales growth, target, production and customer base in which level of mercury represents current value, while the top of the thermometer signifies figure or goal to be achieved. Good thing is that temperature color or level can be used to exhibit or compare different business variables.

Besides this, presenters can also incorporate thermometer metaphors to depict total funds, available funds and used funds.

Download Thermometer PowerPoint Template

5. Circular Infographics

Circular infographics are the most popular and widely used designs in presentation templates. Circular shapes fit well to depict processes that are cyclic in nature thereby making them easy to understand and retain. Best is by applying circular shapes it is easy to portray even complex figures or concepts and hence have a definitive edge over other visuals.

Download Circular Infographic PPT Template

6. Innovative pie-charts

Pie-charts or area diagrams are simple but time tested visual techniques to symbolize different categories of data. In pie-charts arc length is directly proportionate to data and hence resonates perfectly with audience attention. Now, by reducing and increasing the size of each arc proportionately to data a little arty twist can be given to make it more impactful. 

Download Pie-Chart PPT Template

7. Progress Bars

Giving a much richer experience progress bars are a powerful visual tool to illustrate weekly or monthly sales report. Showing completion percentages, progress bars inform spectators how close they are to complete a specific task. In short, as an indicator progress bar lay emphasis that a work is in process. In one line, easily comprehensible colorful visual representation greatly augments audience engagement.

Here’s the sample slide having progress bars to give a picture of various tasks advancement or progression.

Download Progress Bars Diagram

8. Measuring Scale

Every business house undertakes studies to analyze market trends and demand graphs. Here visuals of measuring scales can prove handy to lay emphasis on different findings or values of a survey. Data presented using measuring scale supports audience to make a quick and precise assessment.  

For example, in the sample slide below measuring scale graphics are used to highlight business performance.

Download Measuring Scale PPT Template

Easier to read and understand an icon is a graphical pictogram to indicate a specific subject, thing or expression. Now, icons can also be used to show data in an eye-catching image format. The best thing is that with icons without relying on words presenters can explain data or figures with abstract shapes only.  

For instance, in the slide below icons of humans are used to depict percentages.

Download Icons Chart PowerPoint Template

10. Creative Column Charts

Every second presenter applies vertical bars called column charts to represent data. Each vertical bar in a column chart is proportional to the data value. Application of the column chart is a great choice to show comparisons or data changes. Now, by bringing little arty effects a presenter can make them more likeable.

Download Column Chart PPT Template

Concluding thoughts

Driving audience attention seems harder than ever before. Therefore, a presenter just cannot afford to ignore even the smallest aspect of a PPT like figures or data.

We all know that it takes a lot of efforts to generate authentic figures or data. But getting such figures and presenting them in a PPT presentation is not enough. Presenting figures as such doesn’t mean the job is done.

In fact, that’s when the real work starts – presenting them in a striking manner is also important.    

To conquer this roadblock, a presenter needs to understand the power of data visualization techniques. Key is start using data visualization tricks to make figures or data easily comprehensible even for an ordinary audience.      

To help you out here we have casted a spotlight on ultimate data visualization tricks. Apply them to make your PowerPoint presentation a winning one.

Tell us what your favourite data visualization trick is to make the figures look interesting.  

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

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By Al Boicheva

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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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Data visualization: A detailed guide to visualizing data in your presentation

• Last Updated : October 20, 2023
• 15 Min Read

"The greatest value of a picture is when it forces us to notice what we never expected to see."   - John W. Tukey, mathematician and statistician

Visualization helps decipher or break down information that is challenging to understand in text or numeric form. It's mostly used for data storytelling, as it is a great way to simplify information and present it in a format that is understandable, insightful, and actionable.

Whether you're a data analyst, a graphic designer, a content strategist or a social media manager, expertise in data visualization can help you solve a wide range of business challenges and tell impactful stories. In this blog post, we will look at a step-by-step approach to using data visualizations in your presentation.

What is data visualization?

Data visualization is the process of presenting data in a visual format, such as a chart, graph, or map. It helps users identify patterns and trends in a data set, making it easier to understand complex information. Visualizations can be used to analyze data, make predictions, and even communicate ideas more effectively.

Some examples of data visualizations include dashboards to track analytics, infographics for storytelling, or even word clouds to highlight the crux of your article or script.

Why do we have to visualize data?

In today's information-rich world, audiences are often bombarded with vast amounts of data and complex information. This is where data visualization comes into play—it transforms raw data into visually appealing and comprehensible formats, allowing audiences to grasp key insights and trends at a glance.

Consider the picture below:

The option on the left is a table displaying two categories of data, whereas the option on the right is a graph representing sales growth. As you can see, the chart is more insightful, and makes it easier to identify trends in the numbers.

A good visualization typically represents some form of collected data as a picture, and can help with:

• Faster decision-making
• Identification of patterns and trends
• Presentation of an argument or story

Why is data visualization important in presentations? 

Whether it's a business pitch, a campaign report, or a research presentation, data visualizations help you engage viewers on both rational and emotional levels.

They can be used to evoke empathy, urgency, or excitement, making the content more relatable and compelling. This is particularly crucial in decision-making contexts, where data-driven insights can sway opinions, drive actions, and guide strategic choices.

Ultimately, by incorporating data visualizations into presentations, you can benefit in the following ways:

• Elevate communication and convey impactful, data-centric narratives.
• Tell your story using visuals in a clear and meaningful way.
• Foster a deeper understanding of your data to make a stronger impact on the audience.
• Support idea generation and help derive business insights.
• Simplify data and business processes.

Step-by-step approach to data visualizations in presentations:

There are several factors to consider before adding a data visualization to your presentation. Here's a detailed guide:

Step 1:   Define your purpose

The first step to visualizing data in your presentation is to determine your key message and decide on the type of story you are going to tell. Whether you plan to reveal trends, compare data, or explain a concept, a well-defined purpose will guide your data selection and visualization design, ensuring your visuals play a meaningful role in conveying your message.

Step 2: Understand your audience

Identify who your visualization is meant for and then make sure it fits their needs. Tailor your approach to suit your audience's familiarity with the topic and preferred level of detail. Knowing their expectations will help you fine-tune the complexity and depth of your visualizations, ensuring your presentation truly resonates with your audience.

Step 3: Choose your visualization type

Different data types and relationships call for different visualization formats. Selecting the appropriate chart, graph, or diagram is essential for accurately conveying your information. Here are some visualization types commonly used in presentations:

Tables:  These consist of rows and columns and are used to compare variables in a structured way. Tables display data as categorical objects and make comparative data analysis easier. Example use: Pricing vs. feature comparison table.

Bar charts: Also known as column charts, these chart types use vertical or horizontal bars to compare categorical data. They are mainly used for analyzing value trends. Example use: Measure employee growth within a year.

Pie charts: These graphs are divided into sections that represent parts of a whole. They are used to compare the size of each component and are usually used to determine a percentage of the whole. Example use: Display website visitors by country.

Area charts: These are similar to bar and line graphs and show the progress of values over a period. These are mostly used to showcase data with a time-series relationship, and can be used to gauge the degree of a change in values. Example use: Show sales of different products in a financial year.

Histograms:  Similar to bar charts (but with no space in between), histograms distribute numerical data. They are mainly used to plot the distribution of numbers and analyze the largest frequencies within a particular range. Example use: Measure app users by age.

Scatter charts: Also know as scatter plots, these graphs present the relationship between two variables. They are used to visualize large data sets, and show trends, clusters, patterns, and outliers. Example use: Track performance of different products in a suite.

Heat maps: These are a graphical way to visualize data in the form of hot and cold spots to identify user behavior. Example use: Present visitor behavior on your webpage.

Venn diagrams: These are best for showcasing similarities and differences between two or more categories. They are incredibly versatile and great for making comparisons, unions and intersections of different categories.

Timelines: These are best used for presenting chronological data. This is the most effective and efficient way to showcase events or time passage.

Flowcharts:  These types of charts are ideal for showcasing a process or a workflow.

Infographics: These are a visual representation of content or data in a graphic format to make it more understandable at a glance.

Bonus: In addition to the above mentioned visualization types, you can use Gantt charts, word clouds, and tree maps. Gantt charts are used in project management presentations to demonstrate the work completed in a given period. Word clouds are a graphical representation of word frequency that gives greater prominence to the words that appear most within content. Tree maps display hierarchical data as a set of nested shapes, typically in the shape of rectangles.

Step 4: Use an appropriate chart

Once you're familiar with the different chart types available, the next step is to select the one that best conveys your key message. Knowing when and how to use each chart type empowers you to represent your data accurately and enhances the persuasiveness of your presentation. The best chart type for your needs depends more on the kind of analysis you are targeting than the type of data you've collected. Let's take a look at some of the most-used data visualization approaches in presentations.

Display changes over time: One of the most common applications of data visualizations is to show changes that have occurred over time. Bar or line charts are helpful in these instances.

Illustrate a part-to-whole composition: There might be times when you need to analyze the different components of a whole composition. Use pie, doughnut, and stacked bar charts for these part-to-whole compositions.

Visualize data distribution: Another important use of data visualization is to show how data has been distributed. Scatter plots, bar charts, and histograms help identify the outliers and demonstrate the range of information in the values.

Explore variable relationships: When you want to understand the relationship between two variables, use scatter plots or bubble charts. These can help you depict relationships between two variables, and observe trends and patterns between them.

Compare values between groups: Another common application of data visualization is in comparing values between two distinct groups. Using a grouped bar or line chart makes it easy to understand and compare trends.

There are several types of charts available in Zoho Show, each offering their own advantages. Learn how you can add and edit these charts in Show .

Step 5:  Pick the right visualization tool 

Utilize visualization software or tools that align with your proficiency and presentation needs. Factors such as ease of use, customization options, and compatibility with your data source should influence your choice of tool, enabling you to create impactful visualizations efficiently.

Zoho Show's charts are customizable, easy to use and come with wide range of options to make your data visualization easier. Some of the other prominent data visualization tools include Zoho Analytics ,  Tableau , Power Bi , and Infogram . These tools support a variety of visual styles and are capable of handling a large volume of data.

Step 6: Follow design  best practices 

Applying design principles will help you make sure your visualization is both aesthetically pleasing and easy to understand. You may apply these principles by choosing appropriate font colors and styles, or by effectively labeling and annotating your charts. By adhering to design best practices, you can create polished visuals and amplify the impact of your data-driven narrative.

Keep it simple: Data overload can quickly lead to confusion, so it’s important to include only the important information and simplify complex data. As a rule of thumb, don't crowd your slides with too much data, and avoid distracting elements.

Choose colors wisely:  Use colors to differentiate and highlight information. The best practice is to use contrasting colors. You can also use patterns or texture to convey different types of information—but remember not to distort the data by applying 3D or gradient effects.

Add titles, labels, and annotations:  Be sure to add a title, label, and description to your chart so your audience knows what they are looking at. Remember to keep it clear and concise.

Use proper fonts and text sizes:  Use proper font styles and sizes to label and describe your charts. Your font choices may be playful, sophisticated, attention-grabbing, or elegant. Just be sure to choose a font that is easy to read and appropriate for your key message.

Closing thoughts 

Human brains are naturally attuned to processing visual patterns and imageryUsing visuals not only helps you simplify complex information, but also makes your information more memorable. By leveraging charts and graphs, presenters can convey information to their audiences in a highly comprehensible manner. This helps them offer key insights and contribute to the decision-making process.

Ultimately, by incorporating data visualizations into presentations, presenters can elevate their communication from mere data sharing to impactful storytelling, fostering a deeper understanding of information among their audiences.

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Blog Data Visualization 10 Data Presentation Examples For Strategic Communication

10 Data Presentation Examples For Strategic Communication

Written by: Krystle Wong Sep 28, 2023

Knowing how to present data is like having a superpower. 

Data presentation today is no longer just about numbers on a screen; it’s storytelling with a purpose. It’s about captivating your audience, making complex stuff look simple and inspiring action. 

To help turn your data into stories that stick, influence decisions and make an impact, check out Venngage’s free chart maker or follow me on a tour into the world of data storytelling along with data presentation templates that work across different fields, from business boardrooms to the classroom and beyond. Keep scrolling to learn more! 

Click to jump ahead:

10 Essential data presentation examples + methods you should know

What should be included in a data presentation, what are some common mistakes to avoid when presenting data, faqs on data presentation examples, transform your message with impactful data storytelling.

Data presentation is a vital skill in today’s information-driven world. Whether you’re in business, academia, or simply want to convey information effectively, knowing the different ways of presenting data is crucial. For impactful data storytelling, consider these essential data presentation methods:

1. Bar graph

Ideal for comparing data across categories or showing trends over time.

Bar graphs, also known as bar charts are workhorses of data presentation. They’re like the Swiss Army knives of visualization methods because they can be used to compare data in different categories or display data changes over time. 

In a bar chart, categories are displayed on the x-axis and the corresponding values are represented by the height of the bars on the y-axis. 

It’s a straightforward and effective way to showcase raw data, making it a staple in business reports, academic presentations and beyond.

Make sure your bar charts are concise with easy-to-read labels. Whether your bars go up or sideways, keep it simple by not overloading with too many categories.

2. Line graph

Great for displaying trends and variations in data points over time or continuous variables.

Line charts or line graphs are your go-to when you want to visualize trends and variations in data sets over time.

One of the best quantitative data presentation examples, they work exceptionally well for showing continuous data, such as sales projections over the last couple of years or supply and demand fluctuations. 

The x-axis represents time or a continuous variable and the y-axis represents the data values. By connecting the data points with lines, you can easily spot trends and fluctuations.

A tip when presenting data with line charts is to minimize the lines and not make it too crowded. Highlight the big changes, put on some labels and give it a catchy title.

3. Pie chart

Useful for illustrating parts of a whole, such as percentages or proportions.

Pie charts are perfect for showing how a whole is divided into parts. They’re commonly used to represent percentages or proportions and are great for presenting survey results that involve demographic data. 

Each “slice” of the pie represents a portion of the whole and the size of each slice corresponds to its share of the total. 

While pie charts are handy for illustrating simple distributions, they can become confusing when dealing with too many categories or when the differences in proportions are subtle.

Don’t get too carried away with slices — label those slices with percentages or values so people know what’s what and consider using a legend for more categories.

4. Scatter plot

Effective for showing the relationship between two variables and identifying correlations.

Scatter plots are all about exploring relationships between two variables. They’re great for uncovering correlations, trends or patterns in data. 

In a scatter plot, every data point appears as a dot on the chart, with one variable marked on the horizontal x-axis and the other on the vertical y-axis.

By examining the scatter of points, you can discern the nature of the relationship between the variables, whether it’s positive, negative or no correlation at all.

If you’re using scatter plots to reveal relationships between two variables, be sure to add trendlines or regression analysis when appropriate to clarify patterns. Label data points selectively or provide tooltips for detailed information.

5. Histogram

Best for visualizing the distribution and frequency of a single variable.

Histograms are your choice when you want to understand the distribution and frequency of a single variable. 

They divide the data into “bins” or intervals and the height of each bar represents the frequency or count of data points falling into that interval. 

Histograms are excellent for helping to identify trends in data distributions, such as peaks, gaps or skewness.

Here’s something to take note of — ensure that your histogram bins are appropriately sized to capture meaningful data patterns. Using clear axis labels and titles can also help explain the distribution of the data effectively.

6. Stacked bar chart

Useful for showing how different components contribute to a whole over multiple categories.

Stacked bar charts are a handy choice when you want to illustrate how different components contribute to a whole across multiple categories. 

Each bar represents a category and the bars are divided into segments to show the contribution of various components within each category. 

This method is ideal for highlighting both the individual and collective significance of each component, making it a valuable tool for comparative analysis.

Stacked bar charts are like data sandwiches—label each layer so people know what’s what. Keep the order logical and don’t forget the paintbrush for snazzy colors. Here’s a data analysis presentation example on writers’ productivity using stacked bar charts:

7. Area chart

Similar to line charts but with the area below the lines filled, making them suitable for showing cumulative data.

Area charts are close cousins of line charts but come with a twist. 

Imagine plotting the sales of a product over several months. In an area chart, the space between the line and the x-axis is filled, providing a visual representation of the cumulative total. 

This makes it easy to see how values stack up over time, making area charts a valuable tool for tracking trends in data.

For area charts, use them to visualize cumulative data and trends, but avoid overcrowding the chart. Add labels, especially at significant points and make sure the area under the lines is filled with a visually appealing color gradient.

8. Tabular presentation

Presenting data in rows and columns, often used for precise data values and comparisons.

Tabular data presentation is all about clarity and precision. Think of it as presenting numerical data in a structured grid, with rows and columns clearly displaying individual data points. 

A table is invaluable for showcasing detailed data, facilitating comparisons and presenting numerical information that needs to be exact. They’re commonly used in reports, spreadsheets and academic papers.

When presenting tabular data, organize it neatly with clear headers and appropriate column widths. Highlight important data points or patterns using shading or font formatting for better readability.

9. Textual data

Utilizing written or descriptive content to explain or complement data, such as annotations or explanatory text.

Textual data presentation may not involve charts or graphs, but it’s one of the most used qualitative data presentation examples. 

It involves using written content to provide context, explanations or annotations alongside data visuals. Think of it as the narrative that guides your audience through the data. 

Well-crafted textual data can make complex information more accessible and help your audience understand the significance of the numbers and visuals.

Textual data is your chance to tell a story. Break down complex information into bullet points or short paragraphs and use headings to guide the reader’s attention.

10. Pictogram

Using simple icons or images to represent data is especially useful for conveying information in a visually intuitive manner.

Pictograms are all about harnessing the power of images to convey data in an easy-to-understand way. 

Instead of using numbers or complex graphs, you use simple icons or images to represent data points. 

For instance, you could use a thumbs up emoji to illustrate customer satisfaction levels, where each face represents a different level of satisfaction. 

Pictograms are great for conveying data visually, so choose symbols that are easy to interpret and relevant to the data. Use consistent scaling and a legend to explain the symbols’ meanings, ensuring clarity in your presentation.

Looking for more data presentation ideas? Use the Venngage graph maker or browse through our gallery of chart templates to pick a template and get started! 

A comprehensive data presentation should include several key elements to effectively convey information and insights to your audience. Here’s a list of what should be included in a data presentation:

1. Title and objective

• Begin with a clear and informative title that sets the context for your presentation.
• State the primary objective or purpose of the presentation to provide a clear focus.

2. Key data points

• Present the most essential data points or findings that align with your objective.
• Use charts, graphical presentations or visuals to illustrate these key points for better comprehension.

3. Context and significance

• Provide a brief overview of the context in which the data was collected and why it’s significant.
• Explain how the data relates to the larger picture or the problem you’re addressing.

4. Key takeaways

• Summarize the main insights or conclusions that can be drawn from the data.
• Highlight the key takeaways that the audience should remember.

5. Visuals and charts

• Use clear and appropriate visual aids to complement the data.
• Ensure that visuals are easy to understand and support your narrative.

6. Implications or actions

• Discuss the practical implications of the data or any recommended actions.
• If applicable, outline next steps or decisions that should be taken based on the data.

7. Q&A and discussion

• Allocate time for questions and open discussion to engage the audience.
• Address queries and provide additional insights or context as needed.

Presenting data is a crucial skill in various professional fields, from business to academia and beyond. To ensure your data presentations hit the mark, here are some common mistakes that you should steer clear of:

Overloading with data

Presenting too much data at once can overwhelm your audience. Focus on the key points and relevant information to keep the presentation concise and focused. Here are some free data visualization tools you can use to convey data in an engaging and impactful way. 

Assuming everyone’s on the same page

It’s easy to assume that your audience understands as much about the topic as you do. But this can lead to either dumbing things down too much or diving into a bunch of jargon that leaves folks scratching their heads. Take a beat to figure out where your audience is coming from and tailor your presentation accordingly.

Misleading visuals

Using misleading visuals, such as distorted scales or inappropriate chart types can distort the data’s meaning. Pick the right data infographics and understandable charts to ensure that your visual representations accurately reflect the data.

Not providing context

Data without context is like a puzzle piece with no picture on it. Without proper context, data may be meaningless or misinterpreted. Explain the background, methodology and significance of the data.

Not citing sources properly

Neglecting to cite sources and provide citations for your data can erode its credibility. Always attribute data to its source and utilize reliable sources for your presentation.

Not telling a story

Avoid simply presenting numbers. If your presentation lacks a clear, engaging story that takes your audience on a journey from the beginning (setting the scene) through the middle (data analysis) to the end (the big insights and recommendations), you’re likely to lose their interest.

Infographics are great for storytelling because they mix cool visuals with short and sweet text to explain complicated stuff in a fun and easy way. Create one with Venngage’s free infographic maker to create a memorable story that your audience will remember.

Ignoring data quality

Presenting data without first checking its quality and accuracy can lead to misinformation. Validate and clean your data before presenting it.

Simplify your visuals

Fancy charts might look cool, but if they confuse people, what’s the point? Go for the simplest visual that gets your message across. Having a dilemma between presenting data with infographics v.s data design? This article on the difference between data design and infographics might help you out. 

Missing the emotional connection

Data isn’t just about numbers; it’s about people and real-life situations. Don’t forget to sprinkle in some human touch, whether it’s through relatable stories, examples or showing how the data impacts real lives.

Skipping the actionable insights

At the end of the day, your audience wants to know what they should do with all the data. If you don’t wrap up with clear, actionable insights or recommendations, you’re leaving them hanging. Always finish up with practical takeaways and the next steps.

Can you provide some data presentation examples for business reports?

Business reports often benefit from data presentation through bar charts showing sales trends over time, pie charts displaying market share,or tables presenting financial performance metrics like revenue and profit margins.

What are some creative data presentation examples for academic presentations?

Creative data presentation ideas for academic presentations include using statistical infographics to illustrate research findings and statistical data, incorporating storytelling techniques to engage the audience or utilizing heat maps to visualize data patterns.

What are the key considerations when choosing the right data presentation format?

When choosing a chart format , consider factors like data complexity, audience expertise and the message you want to convey. Options include charts (e.g., bar, line, pie), tables, heat maps, data visualization infographics and interactive dashboards.

Knowing the type of data visualization that best serves your data is just half the battle. Here are some best practices for data visualization to make sure that the final output is optimized. 

How can I choose the right data presentation method for my data?

To select the right data presentation method, start by defining your presentation’s purpose and audience. Then, match your data type (e.g., quantitative, qualitative) with suitable visualization techniques (e.g., histograms, word clouds) and choose an appropriate presentation format (e.g., slide deck, report, live demo).

For more presentation ideas , check out this guide on how to make a good presentation or use a presentation software to simplify the process.  

How can I make my data presentations more engaging and informative?

To enhance data presentations, use compelling narratives, relatable examples and fun data infographics that simplify complex data. Encourage audience interaction, offer actionable insights and incorporate storytelling elements to engage and inform effectively.

The opening of your presentation holds immense power in setting the stage for your audience. To design a presentation and convey your data in an engaging and informative, try out Venngage’s free presentation maker to pick the right presentation design for your audience and topic. 

What is the difference between data visualization and data presentation?

Data presentation typically involves conveying data reports and insights to an audience, often using visuals like charts and graphs. Data visualization , on the other hand, focuses on creating those visual representations of data to facilitate understanding and analysis. 

Now that you’ve learned a thing or two about how to use these methods of data presentation to tell a compelling data story , it’s time to take these strategies and make them your own. 

But here’s the deal: these aren’t just one-size-fits-all solutions. Remember that each example we’ve uncovered here is not a rigid template but a source of inspiration. It’s all about making your audience go, “Wow, I get it now!”

Think of your data presentations as your canvas – it’s where you paint your story, convey meaningful insights and make real change happen. 

So, go forth, present your data with confidence and purpose and watch as your strategic influence grows, one compelling presentation at a time.

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From Data to Insights: Data Visualization in PowerPoint

In the age of information, data is abundant. Whether you’re a business professional, a researcher, or a student, you often need to convey complex data in a clear and understandable manner. This is where the art of data visualization comes into play. Data visualization in PowerPoint can transform raw numbers into meaningful insights that resonate with your audience. In this blog post, we’ll explore the importance of data visualization and how to effectively use it in your PowerPoint presentations.

Why Data Visualization Matters

Data visualization is the practice of representing data through charts, graphs, and other visual elements. It’s an essential tool for turning data into insights for several reasons:

• Clarity : Visualizing data makes it easier to understand and interpret. A well-designed chart or graph can convey complex information more effectively than a table of numbers.
• Engagement : Visuals capture and hold your audience’s attention. They make your presentation more engaging and memorable.
• Storytelling : Data visualization helps you tell a story with your data. You can highlight trends, correlations, and outliers, providing a compelling narrative.

Choosing the Right Visualization

The first step in data visualization is selecting the right type of chart or graph for your data. PowerPoint provides various options, including:

• Bar charts : Great for comparing data across categories.
• Line charts : Ideal for showing trends over time.
• Pie charts : Useful for illustrating parts of a whole.
• Scatter plots : Good for showing relationships between two variables.
• Heat maps : Effective for displaying patterns and variations.

Choose the visualization method that best conveys your data’s message. Remember, not every data point needs a visualization; only use visuals for the most crucial information.

Design Principles for Effective Data Visualization

Creating impactful data visualizations in PowerPoint requires adherence to some design principles:

• Simplicity : Keep your visuals clean and uncluttered. Remove unnecessary elements that don’t contribute to the message.
• Consistency : Maintain a consistent color scheme and style throughout your presentation. This creates a cohesive look and reinforces your brand.
• Labeling : Always label your axes, data points, and any significant features. Clarity is essential to understanding the data.
• Color : Use color purposefully. Avoid using too many colors, as it can confuse the audience. Ensure your color choices are accessible for all viewers, including those with color vision deficiencies.
• Legibility : Ensure your text is readable, even when projected. Use a legible font size and style, and contrast your text with the background.

Telling a Data-Driven Story

Data visualization should be an integral part of your presentation’s narrative. Here’s how you can incorporate it effectively:

• Start with a Hook : Begin your presentation with an engaging data visualization that teases your main findings or insights.
• Contextualize : Provide context for your data. Explain what the numbers represent and why they matter.
• Use Data as Evidence : Use data to support your arguments and claims. Visuals make your case more compelling.
• Highlight Key Points : Emphasize the most critical data points using visual cues like color, size, or annotations.
• Summarize and Conclude : End your presentation with a summary visualization that highlights your main insights and conclusions.

Data visualization in PowerPoint is a powerful tool for turning raw data into actionable insights. By choosing the right visualization methods and following design principles, you can create engaging, informative, and persuasive presentations. Remember that the goal is not just to present data but to provide your audience with the tools they need to understand, interpret, and act on that data. So, from your next PowerPoint presentation onward, make data your ally in delivering impactful insights to your audience.

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The Ultimate Guide to Data Visualization

Data visualization is important because it breaks down complex data and extracts meaningful insights in a more digestible way. Displaying the data in a more engaging way helps audiences make sense of the information with a higher chance of retention. But with a variety of charts and graphs, how can you tell which is best for your specific content and audience?

Consider this your ultimate guide to data visualization. We’re breaking down popular charts and graphs and explaining the differences between each so that you can choose the best slide for your story. 

Charts vs. graphs

We know that numbers don’t lie and are a strong way to back up your story, but that doesn’t always mean they’re easy to understand. By packaging up complex numbers and metrics in visually appealing graphics you’re telling your audience exactly what they need to know without having to rack their brain to comprehend it. Graphs and charts are important in your presentation because they take your supporting statistics, and story, and make them more relatable. 

Charts present data or complex information through tables, infographics , and diagrams, while graphs show a connection between two or more sets of data.

A histogram is a visual representation of the distribution of data. The graph itself consists of a set of rectangles— each rectangle represents a range of values (called a "bin"), while the height corresponds to the numbers of the data that fall within that range.

Histograms are oftentimes used to visualize the frequency distribution of continuous data. Things such as measurements of height, weight, or time can all be organized in the graph. They can also be used to display the distribution of discrete data, like the number of shoes sold in a shoe department during any given period of time.

Histograms are a useful tool for analyzing data, as they allow you to quickly see the shape of the data distribution, the location of the central tendency (the mean or median), and the full spread of the data. They’re a great chart that can also reveal any changes in the data, making it easier to digest.

Need to add a little visual interest to your business presentation? A bar graph slide can display your data easily and effectively. Whether you use a vertical bar graph or horizontal bar graph, a bar graph gives you options to help simplify and present complex data, ensuring you get your point across.

Use it to track long-term changes.

Vertical bar graphs are great for comparing different groups that change over a long period of time. Small or short-term changes may not be as obvious in bar graph form.

Don’t be afraid to play with design .

You can use one bar graph template slide to display a lot of information, as long as you differentiate between data sets. Use colors, spacing, and labels to make the differences obvious.

Use a horizontal graph when necessary.

If your data labels are long, a horizontal bar graph may be easier to read and organize than a vertical bar graph. 

Don’t use a horizontal graph to track time.

A vertical bar graph makes more sense when graphing data over time, since the x-axis is usually read from left to right.

Histograms vs. bar graphs

While a histogram is similar to a bar graph, it groups numbers into ranges and displays data in a different way.

Bar graphs are used to represent categorical data, where each bar represents a different category with a height or length proportional to the associated value. The categories of a bar graph don’t overlap, and the bars are usually separated by a gap to differentiate from one another. Bar graphs are ideal when you need to compare the data of different categories.

On the other hand, histograms divide data into a set of intervals or "bins". The bars of a histogram are typically adjacent to each other, with no gaps, as the bins are continuous and can overlap. Histograms are used to visualize the shape, center, and spread of a distribution of numerical data.

A pie chart is a circular graph (hence the name ‘pie’) that’s used to show or compare different segments — or ‘slices’ — of data. Each slice represents a proportion that relates to the whole. When added up, each slice should equal the total. Pie charts are best used for showcasing part-to-whole relationships. In other words, if you have different parts or percentages of a whole, using a pie chart is likely the way to go. Just make sure the total sum equals 100%, or the chart won’t make a lot of sense or convey the message you want it to. Essentially, any type of content or data that can be broken down into comparative categories is suitable to use. Revenue, demographics, market shares, survey results — these are just a few examples of the type of content to use in a pie chart. However, you don’t want to display more than six categories of data or the pie chart can be difficult to read and compare the relative size of slices. 

Donut Charts

A donut chart is almost identical to a pie chart, but the center is cut out (hence the name ‘donut’). Donut charts are also used to show proportions of categories that make up the whole, but the center can also be used to display data. Like pie charts, donut charts can be used to display different data points that total 100%. These are also best used to compare a handful of categories at-a-glance and how they relate to the whole. The same type of content you’d use for a pie chart can also work for a donut chart. However, with donut charts, you have room for fewer categories than pie charts — anywhere from 2 to 5. That’s because you want your audience to be able to quickly tell the difference between arc lengths, which can help tell a more compelling story and get your point across more efficiently. 

Pie charts vs. donut charts

You may notice that a donut chart and a pie chart look almost identical . While a donut chart is essentially the same as a pie chart in function, with its center cut out, the “slices” in a donut chart are sometimes more clearly defined than in a pie chart.

When deciding between a pie chart or a donut chart for your presentation, make sure the data you’re using is for comparison analysis only. Pie and donut charts are usually limited to just that — comparing the differences between categories. The easiest way to decide which one to use? 

The number of categories you’re comparing. If you have more than 4 or 5 categories, go with a pie chart. If you have between 2 and 4 categories, go with a donut chart. Another way to choose? If you have an extra data point to convey (e.g. all of your categories equal an increase in total revenue), use a donut chart so you can take advantage of the space in the middle.

Comparison charts

As its name implies, a comparison chart or comparison graph draws a comparison between two or more items across different parameters. You might use a comparison chart to look at similarities and differences between items, weigh multiple products or services in order to choose one, or present a lot of data in an easy-to-read format.

For a visually interesting twist on a plain bar chart, add a data comparison slide to your presentation. Our data comparison template is similar to a bar graph, using bars of varying lengths to display measured data. The data comparison template, however, displays percentages instead of exact numbers. One of the best things about using Beautiful.ai’s data comparison slide? You can customize it for your presentation. Create a horizontal or vertical slide, remove or add grid lines, play with its design, and more.

Gantt charts

A Gantt chart , named after its early 20th century inventor Henry Gantt, is a birds-eye view of a project. It visually organizes tasks displayed over time. Gantt charts are incredibly useful tools that work for projects and groups of all sizes. 

It’s a type of bar chart that you would use to show the start and finish dates of several elements of a project such as what the project tasks are, who is working on each task, how long each task will take, and how tasks group together, overlap, and link with each other. The left side of a Gantt chart lists each task in a project by name. Running along the top of the chart from left to right is a timeline. Depending on the demands and details of your project, the timeline may be broken down by quarter, month, week, or even day.

Project management can be complex, so it’s important to keep your chart simple by using a color scheme with cool colors like blues or greens. You can color code items thematically or by department or person, or even highlight a single task with a contrasting color to call attention to it. You can also choose to highlight important tasks using icons or use images for other annotations. This will make your chart easier to read and more visually appealing. 

Additional tips for creating an effective Gantt chart slide .

Use different colors

How many colors you use and how you assign them is up to you. You might choose one color to represent a specific team or department so that you can see who is responsible for which tasks on your chart, for example. 

Set milestones

Don’t forget to set milestones where they make sense: deadlines required by clients or customers, when a new department takes over the next phase of the project, or when a long list of tasks is completed. 

Label your tasks

When used with a deliberate color scheme, labeling your tasks with its project owner will prevent confusion and make roles clear to everyone. 

Jordan Turner

Jordan is a Bay Area writer, social media manager, and content strategist.

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The step-by-step approach to data visualization in presentations

We live in an age of digital information flow. Credibility and verifiability are important currencies when it comes to conveying information. While facts and figures have gained new significance, they often struggle to get noticed alongside the much better performing visual content.

Data visualization is the art of converting contexts, circumstances, and developments derived from verifiable data into visual objects in such a way that they are, ideally, graspable and comprehensible right from the first glance. Infographics, pie charts, bar graphs, or radar charts are all popular formats.

But how can larger volumes of data also be used to paint an informative picture? In five steps, we’ll explain what you need to remember when creating charts, diagrams, and graphs.

The data assessment

Companies generally have access to a wide range of data. Be selective when choosing the data you want to communicate. Assess the informative value and knowledge gain offered by the data sets. When it comes to graphs, charts and diagrams, the same approach applies as for all other PowerPoint-presentation content: Keep your presentation as short and concise as possible, and avoid overloading it with superfluous information.

Data is relevant if, for example:

• It shows developments that enable forecasts to be made for the future.
• It describes pattern deviations that indicate changes in trends.
• It highlights contexts/correlations previously unheard of.
• It confirms previously unverifiable assumptions. 

Our tip: If you’re not sure whether certain data is important for your presentation, put it on a backup slide or in the appendix. If a relevant discussion or question comes up during your presentation, you can instantly access it then. This will show you’re well prepared and have thought your presentation through very carefully. And can focus on what’s most important for your audience.

The message

Data is often multidimensional, which makes it complex and difficult to understand. When it comes to data visualization, it is important to concentrate on the main findings and make clear, simple statements. But this also means you need to leave out anything that’s unnecessary. Excessive detail does not make a chart better. A core statement is not made more concise by having extra aspects added on to it. When handling data, people often fall into the trap of following an almost scientific approach. But most business presentations are not of a scientific nature; they’re about key findings. And the more scaled back these are, the clearer they become.

Our tip: Do you feel like you lose too much information by reducing data to a single message? Then check whether you can address the individual aspects separately. Make the most of visual storytelling, and combine various data representations into a well-structured narrative.

The target audience

Carefully consider the target audience of your presentation, and think about how familiar they are with handling data. While data is seen as proof of certain statements, it often also raises new questions. Always state the data source, and be prepared for questions about the collection method, time frame, and contexts/correlations.

Try not to overwhelm your target audience. Remember, even though you’ve been working with the tables and charts for a long time, this is the first time your audience will be seeing them.

Our tip: Remember the 15-second rule for presenting data. Anything that doesn’t trigger a “lightbulb moment” among your target audience within this time frame is definitely too complex. Test it on your coworkers and scale back your information if necessary.

When visualizing your data, only apply principles that will help your audience navigate and grasp the message. Making a table colorful because it looks nicer is not constructive; it might even end up being confusing. The human brain takes in lots of information subconsciously and sorts it. And there are certain perception principles you can utilize. Give your audience whatever they need to understand and easily grasp what you are showing, such as:

• A clear verbal introduction
• A clear heading conveying the slide’s core statement
• Colors of emotional significance (red=danger, yellow=neutral, green=desirable, corporate colors and competitor colors)
• Logical reading order (left to right and clockwise, e.g. based on importance and percentage in a pie chart)
• Labelling and accompanying texts reduced to the absolutely necessary, avoid repetition
• Learned symbols, e.g. symbols for female and male or flags
• Important information highlighted—using size, color, or distinguishing elements

Implementation

Only once you are familiar with your data and have identified the main statement can you determine the type of data suitable. It’s not just the visual attractiveness of a display format that is crucial; its function is too. Situations can be shown differently to processes. Contexts/correlations require a different format to percentages. A list of the most common display formats and their areas of use is available  here .

When visualizing your data, be sure to take into account your company’s corporate design. PowerPoint masters are unfortunately often patchy when it comes to data visualization. This is a shame, because uniformly designed tables and charts convey a sense of professionalism, and underline the credibility of the information. Data visualizations are a key part of branding.

Contact us  if you want to know how to professionally create data in your corporate design in PowerPoint.

Also remember our 5 criteria for successful PowerPoint presentations, and follow the  OSCAR principle , which can also be applied to data visualization.

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Data Visualization Best Practices Presentation

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This slideshow provides general best practices for working with data visualizations meant for display in print or digital publication or slideshow presentations. Dowload by clicking the file name above, or view in the document reader below.

Data visualization is the representation of data through use of common graphics, such as charts, plots, infographics and even animations. These visual displays of information communicate complex data relationships and data-driven insights in a way that is easy to understand.

Data visualization can be utilized for a variety of purposes, and it’s important to note that is not only reserved for use by data teams. Management also leverages it to convey organizational structure and hierarchy while data analysts and data scientists use it to discover and explain patterns and trends.  Harvard Business Review  (link resides outside ibm.com) categorizes data visualization into four key purposes: idea generation, idea illustration, visual discovery, and everyday dataviz. We’ll delve deeper into these below:

Idea generation

Data visualization is commonly used to spur idea generation across teams. They are frequently leveraged during brainstorming or  Design Thinking  sessions at the start of a project by supporting the collection of different perspectives and highlighting the common concerns of the collective. While these visualizations are usually unpolished and unrefined, they help set the foundation within the project to ensure that the team is aligned on the problem that they’re looking to address for key stakeholders.

Idea illustration

Data visualization for idea illustration assists in conveying an idea, such as a tactic or process. It is commonly used in learning settings, such as tutorials, certification courses, centers of excellence, but it can also be used to represent organization structures or processes, facilitating communication between the right individuals for specific tasks. Project managers frequently use Gantt charts and waterfall charts to illustrate  workflows .  Data modeling  also uses abstraction to represent and better understand data flow within an enterprise’s information system, making it easier for developers, business analysts, data architects, and others to understand the relationships in a database or data warehouse.

Visual discovery

Visual discovery and every day data viz are more closely aligned with data teams. While visual discovery helps data analysts, data scientists, and other data professionals identify patterns and trends within a dataset, every day data viz supports the subsequent storytelling after a new insight has been found.

Data visualization

Data visualization is a critical step in the data science process, helping teams and individuals convey data more effectively to colleagues and decision makers. Teams that manage reporting systems typically leverage defined template views to monitor performance. However, data visualization isn’t limited to performance dashboards. For example, while  text mining  an analyst may use a word cloud to to capture key concepts, trends, and hidden relationships within this unstructured data. Alternatively, they may utilize a graph structure to illustrate relationships between entities in a knowledge graph. There are a number of ways to represent different types of data, and it’s important to remember that it is a skillset that should extend beyond your core analytics team.

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The earliest form of data visualization can be traced back the Egyptians in the pre-17th century, largely used to assist in navigation. As time progressed, people leveraged data visualizations for broader applications, such as in economic, social, health disciplines. Perhaps most notably, Edward Tufte published  The Visual Display of Quantitative Information  (link resides outside ibm.com), which illustrated that individuals could utilize data visualization to present data in a more effective manner. His book continues to stand the test of time, especially as companies turn to dashboards to report their performance metrics in real-time. Dashboards are effective data visualization tools for tracking and visualizing data from multiple data sources, providing visibility into the effects of specific behaviors by a team or an adjacent one on performance. Dashboards include common visualization techniques, such as:

• Tables: This consists of rows and columns used to compare variables. Tables can show a great deal of information in a structured way, but they can also overwhelm users that are simply looking for high-level trends.
• Pie charts and stacked bar charts:  These graphs are divided into sections that represent parts of a whole. They provide a simple way to organize data and compare the size of each component to one other.
• Line charts and area charts:  These visuals show change in one or more quantities by plotting a series of data points over time and are frequently used within predictive analytics. Line graphs utilize lines to demonstrate these changes while area charts connect data points with line segments, stacking variables on top of one another and using color to distinguish between variables.
• Histograms: This graph plots a distribution of numbers using a bar chart (with no spaces between the bars), representing the quantity of data that falls within a particular range. This visual makes it easy for an end user to identify outliers within a given dataset.
• Scatter plots: These visuals are beneficial in reveling the relationship between two variables, and they are commonly used within regression data analysis. However, these can sometimes be confused with bubble charts, which are used to visualize three variables via the x-axis, the y-axis, and the size of the bubble.
• Heat maps:  These graphical representation displays are helpful in visualizing behavioral data by location. This can be a location on a map, or even a webpage.
• Tree maps, which display hierarchical data as a set of nested shapes, typically rectangles. Treemaps are great for comparing the proportions between categories via their area size.

Access to data visualization tools has never been easier. Open source libraries, such as D3.js, provide a way for analysts to present data in an interactive way, allowing them to engage a broader audience with new data. Some of the most popular open source visualization libraries include:

• D3.js: It is a front-end JavaScript library for producing dynamic, interactive data visualizations in web browsers.  D3.js  (link resides outside ibm.com) uses HTML, CSS, and SVG to create visual representations of data that can be viewed on any browser. It also provides features for interactions and animations.
• ECharts:  A powerful charting and visualization library that offers an easy way to add intuitive, interactive, and highly customizable charts to products, research papers, presentations, etc.  Echarts  (link resides outside ibm.com) is based in JavaScript and ZRender, a lightweight canvas library.
• Vega:   Vega  (link resides outside ibm.com) defines itself as “visualization grammar,” providing support to customize visualizations across large datasets which are accessible from the web.
• deck.gl: It is part of Uber's open source visualization framework suite.  deck.gl  (link resides outside ibm.com) is a framework, which is used for  exploratory data analysis  on big data. It helps build high-performance GPU-powered visualization on the web.

With so many data visualization tools readily available, there has also been a rise in ineffective information visualization. Visual communication should be simple and deliberate to ensure that your data visualization helps your target audience arrive at your intended insight or conclusion. The following best practices can help ensure your data visualization is useful and clear:

Set the context: It’s important to provide general background information to ground the audience around why this particular data point is important. For example, if e-mail open rates were underperforming, we may want to illustrate how a company’s open rate compares to the overall industry, demonstrating that the company has a problem within this marketing channel. To drive an action, the audience needs to understand how current performance compares to something tangible, like a goal, benchmark, or other key performance indicators (KPIs).

Know your audience(s): Think about who your visualization is designed for and then make sure your data visualization fits their needs. What is that person trying to accomplish? What kind of questions do they care about? Does your visualization address their concerns? You’ll want the data that you provide to motivate people to act within their scope of their role. If you’re unsure if the visualization is clear, present it to one or two people within your target audience to get feedback, allowing you to make additional edits prior to a large presentation.

Choose an effective visual:  Specific visuals are designed for specific types of datasets. For instance, scatter plots display the relationship between two variables well, while line graphs display time series data well. Ensure that the visual actually assists the audience in understanding your main takeaway. Misalignment of charts and data can result in the opposite, confusing your audience further versus providing clarity.

Keep it simple:  Data visualization tools can make it easy to add all sorts of information to your visual. However, just because you can, it doesn’t mean that you should! In data visualization, you want to be very deliberate about the additional information that you add to focus user attention. For example, do you need data labels on every bar in your bar chart? Perhaps you only need one or two to help illustrate your point. Do you need a variety of colors to communicate your idea? Are you using colors that are accessible to a wide range of audiences (e.g. accounting for color blind audiences)? Design your data visualization for maximum impact by eliminating information that may distract your target audience.

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Present Your Data Like a Pro

by Joel Schwartzberg

Summary .   

While a good presentation has data, data alone doesn’t guarantee a good presentation. It’s all about how that data is presented. The quickest way to confuse your audience is by sharing too many details at once. The only data points you should share are those that significantly support your point — and ideally, one point per chart. To avoid the debacle of sheepishly translating hard-to-see numbers and labels, rehearse your presentation with colleagues sitting as far away as the actual audience would. While you’ve been working with the same chart for weeks or months, your audience will be exposed to it for mere seconds. Give them the best chance of comprehending your data by using simple, clear, and complete language to identify X and Y axes, pie pieces, bars, and other diagrammatic elements. Try to avoid abbreviations that aren’t obvious, and don’t assume labeled components on one slide will be remembered on subsequent slides. Every valuable chart or pie graph has an “Aha!” zone — a number or range of data that reveals something crucial to your point. Make sure you visually highlight the “Aha!” zone, reinforcing the moment by explaining it to your audience.

With so many ways to spin and distort information these days, a presentation needs to do more than simply share great ideas — it needs to support those ideas with credible data. That’s true whether you’re an executive pitching new business clients, a vendor selling her services, or a CEO making a case for change.

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Data Visualization: Understanding How To Visualize Your Data

• PowerPoint Tutorials
• Charts & Data Viz
• April 22, 2019

What is data visualization?

• 90% of the information transmitted to the brain is visual
• Humans process images 60,000 times faster than text
• 70% of our sensory receptors are in our eyes
• 65% of people are visual learners

Why is data visualization important?

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2. Gives meaning to your data

3. Saves time

Instead of spending the time trying to figure out what the facts and figures mean, your audience members can ENGAGE with the meaning. A visual representation allows you to analyze huge amounts of info in the blink of an eye. As we know, the human eye can recognize and process visual information much faster than text.

4. Makes for better decision making

Assuming your data visualizations contain correct data and are done properly, you’ll not only be able to make decisions faster, but they will be based on data that you fully comprehend.

5. Is more shareable and digestible

One of the best things about data visualization is that they are accessible and easier to share across departments, with colleagues, your boss, or with a large audience. They can be inserted in your PowerPoint presentation, printed for seminar handouts, or even posted and shared on social media.

For example, below is a data visualization superimposing the Titanic over the world’s new cruise ship (the Allure of the Seas) to demonstrate that the new ship is almost 5 times bigger.

Data Visualization Examples

As stated in the research report “ Information Animation Applications in the Capital Markets ,”

The impact of your visual data is only be good as the visualisation! Here are a few great examples of successful data visualizations to give you an idea of the best way to deliver complex information through visuals:

http://www.visualinformation.info/visualizing-the-national-debt-infographic/

It’s important to choose the right visualization for the right information. Here are some of the most common data visualization techniques:

Column Chart Example

Bar charts are one of the most popular data visualizations and most commonly used for comparing items over a horizontal time frame, moving left to right.

These specific data visualizations usually work best with less than 15 data points. If you have more than 15 data points, I recommend using a line chart instead.

You will see this type of data frequently used for showing sales figures over a specific time period, with the years running along the x-axis and the unit running along the Y axis, as you can see in the example below showing Apple’s Revenue from 2014 to 2018.

Bar Chart Example

Similar to the bar chart, the column chart is used to compare multiple values outside of a horizontal based time frame.

This works well for survey data, responses or any other non-date based category. For this type of data visualization you will see the category running up and down

You can also use two different column charts to show how a category has changed over a specific time period.

The two-sided bar chart is a great way to show changes in specific categories over two specific time periods, without having to show all of the information in between those two dates.

Pie Chart and Doughnut Chart Examples

Another familiar visualization technique is the humble doughnut chart (one step better than a pie chart).

The key to making your doughnut charts or pie charts clearer, is to break down your data into two pieces of data to highlight the point you want to make.

For example, if you point is that 85% of survey respondents are using 4 or 5 programs, combine those pieces together and highlight it again the other data as contrasted in the visual below.

Timeline Example

A timeline is a great data visualization technique when you wish to show data in a chronological order and highlighting those important points in time.

To create a Timeline, simply layout your data points along a PowerPoint shape, and mark the data off to visually see your overall project.

If you need to create lots of time based timelines like this, I recommend checking out  Office Timeline . Their PowerPoint app makes creating timelines and Gantt charts extremely easy.

Venn Diagram Example

The Venn Diagram is a great technique for comparing and contrasting ideas and concepts, especially when showing an overlapping piece is important.

For example, in the simple Venn diagram below, your point could be that for a successful launch, you need strategy, execution and commitment.

For help making a Venn diagram in PowerPoint, read our guide here .

Gantt Chart Example

Gantt Charts are particularly useful for project managers as a visualisation technique to show when different phases of a project are starting and stopping over a specific timeline.

Below is an example of a Gantt chart (with a timeline) built entirely using PowerPoint shapes.

Gantt charts like this allow you to organize tasks, team members, timing, potential problems, etc.

They can also be useful for showing multiple categories of continuous data over a period of time.

Infographic Example

Infographics are the business buzzword of the moment. Infographics are a great way to deliver facts and figures in a narrative format which is both attractive and easy to read. They are particularly useful to explain case studies or to summarize complex reports.

You can create your own infographic simply by adding icons, graphics, charts, and formatting your numbers in interesting ways.

Below is an example of a simple infographic I created in Microsoft PowerPoint using nothing but the default PowerPoint icons, fonts and charts. You can obviously make them more complicated if you like.

The goal of an infographic like this is to break down your data points into something visual so that users can more easily digest the information you are presenting them.

Dashboard Data Visualization Example

A dashboard is a data visualization that brings multiple pieces of data (charts, graphics, etc.) onto a single slide. That way you can show the overall health of a situation instead of just individual pieces. Or as explained by Smart Data Collective’s Keyan Keihani.

To create a dashboard, simply create individual graphics of the relevant data points you need to see the overall health or performance of your topic.

For example, your dashboard could be as simple as 3 column charts showing annual sales, annual expenses and annual net income as shown below.

To keep the above dashboard consistent, I used the same vertical axis value of 130 billion. That way the data stays consistent across all 3 column charts. I also used a darker color to highlight the year 2020.

Data Visualization Tips

Don’t forget to be specific in your titles.

While data visualization helps your audience understand your data more easily, you’ll still want to label it well. If you don’t properly label your graphics, your entire meaning can be lost.

Give your graph or chart a title and it instantly becomes more readable.

Highlight your main points clearly

Highlighting certain figures, sections or columns helps draw attention to the most essential information and can direct your message.

Add rectangles or to emphasis your main points

Add a ‘call out’ to highlight your main point

Use colors to highlight your main points

Simplify your pie charts.

When presenting complex information, the right data visualizations are critical to the success of your presentation.

The best data in the world won’t save you unless you present it in a way that people can understand.

So the next time you plan on presenting complex information, it’s worth taking the time to create the right visualization.

To learn more about our PowerPoint training and other free presentation resources,  visit us here .

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A Comprehensive Guide to Data Visualization for Business Analysts

Linlong Wang

Sep 24, 2024

Introduction

In today’s data-driven business environment, effective data visualization is a crucial skill for business analysts. By presenting data visually—through graphs, charts, and interactive dashboards—business analysts not only simplify intricate data but also make patterns, trends, and anomalies more accessible, allowing stakeholders to make faster, informed decisions. Without proper visual representation, even the most profound findings can be lost in translation. Data visualization allows analysts to tell compelling stories, reveal hidden trends, and drive actionable business decisions.

Understanding the Basics of Data Visualization

What is data visualization.

Data visualization involves the design and creation of graphic representations that make large, complex sets of quantitative and qualitative data easier to communicate and understand. Using static, dynamic, or interactive visual elements, these visualizations present data from specific fields of expertise in a way that is accessible to a wider audience. The goal is to enable users to visually explore and quickly grasp key insights, such as patterns, relationships, trends, outliers, and other structures within the data that might be difficult to detect otherwise.

Types of Data Visualization

There are several types of data visualizations, each serving different purposes:

Bar Charts: Ideal for comparing categories of data.

Line Graphs: Useful for showing trends over time.

Pie Charts: Great for illustrating proportions.

Heatmaps: Perfect for highlighting the intensity of data values in a dataset.

Scatter Plots: Excellent for visualizing relationships between variables.

Each of these visual tools has its strengths and is suitable for different kinds of data stories.

Best Practices for Creating Effective Visualizations

Know your audience.

The first step in creating an impactful visualization is understanding who will be viewing it. A dashboard for a team of data scientists will look different from one designed for the executive team. Tailor your visualizations based on the audience’s level of data literacy, their interests, and their needs.

Choosing the Right Visualization for the Data

Not all data fits well into every type of visualization. A clear understanding of the dataset’s nature will help in selecting the appropriate visual tool. For example, categorical data is best represented in bar charts, while continuous data might be more informative in a line graph or histogram.

Design Principles

Good visual design enhances comprehension. Here are some design principles to keep in mind:

Simplicity: Avoid clutter. Too much information in a single visualization can confuse rather than inform.

Consistency: Use consistent color schemes and fonts across multiple visualizations.

Highlight Key Information: Make the most critical insights stand out using size, color, or labels.

Data Visualization Tools for Business Analysts

Overview of popular tools.

There are numerous data visualization tools available, each with its own strengths. Some popular tools include:

Tableau : A powerful platform known for its flexibility and advanced features.

Powerdrill : A rising star in the data visualization space, especially for business analysts, thanks to its ease of use and powerful functionality.

Power BI : Microsoft’s robust tool for visualizing data from various sources.

Google Data Studio : A free and accessible tool for basic visualizations.

How Powerdrill can be used to analyze and present data?

Powerdrill stands out due to its seamless integration with data processing workflows and a wide range of visualization options. The platform offers a user-friendly interface that makes it easy to create impactful visualizations for various business purposes. Here are a few examples of how Powerdrill can be used to analyze and present data from a retail database .

Example 1: Sales by Product Category

This bar chart highlights the total sales across different product categories. By using Powerdrill’s filtering and sorting options, This insight can help the business identify and focus on top-selling products.

Example 2: Monthly Sales Trends

In this line graph, you can see a monthly trend of sales over the past year. Business analysts can forecast future sales and adjust inventory according to the seasonal patterns and growth trends.

Example 3: Relationship Between Customer Spending Frequency and Purchase Amount

This scatterplot reveals the relationship between how frequently customers make purchases and the amount they spend per transaction. The plot helps identify high-value customers who make frequent, large purchases, offering valuable insight for loyalty programs or targeted marketing efforts.

Example 4: Product Combination Sales Comparison

This heatmap showcases the sales performance of various product combinations. By comparing different categories side by side, business analysts can easily spot complementary products or bundles that boost sales, helping with inventory planning and promotional strategies.

Effective data visualization can make or break business decisions. By presenting data in a clear and visually engaging way, analysts can ensure that decision-makers are not only informed but also able to act quickly on insights. A well-crafted visualization reduces uncertainty, highlights key performance indicators, and can even spark innovation within a company.

Now is the time to take your data visualization skills to the next level. Whether you’re new to data visualization or looking to refine your abilities, explore the tools and best practices mentioned here. Dive into Powerdrill tutorials and experiment with different types of visualizations to communicate data effectively and drive better business outcomes. The power of visual storytelling is at your fingertips—use it to transform how your organization makes decisions.

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Visual presentation: tips, techniques, and tools for success

Get your team on prezi – watch this on demand video.

Anete Ezera September 26, 2024

Through the years, communication has grown to be more visual. Presentations that are purely spoken seem to be out of date. With tools like Prezi , we can express our ideas via immersive visual stories and pass our message in a more effective way to resonate better with the audience.

That’s why in this article, we’ll explore what is a visual presentation and the best practices for turning your ideas into visual narratives. Also, we’ll display helpful examples to get inspired by. Let’s dive right in!

What is a visual presentation?

A visual presentation is one that contains visual elements that complement the message you’re conveying. This could be incorporating images, videos, graphs or charts. The reason visual aids in presentations are so effective is because they can display information or data in a way that’s visually pleasing and help to back up the points you’re making. 

There are several types of visual presentations which each serve different purposes and audiences:

• Slideshows : This is the most common form of visual presentation. It typically uses slides or frames containing images, text, and charts.
• Infographics : Infographics can display complex data in a way that’s easy to understand. They’re ideal for summerizing information and making it appear in a more engaging way. 
• Interactive presentations : Interactive presentations allow the audience to play a key role. For example, they can click through different parts of the presentation or use drag-and-drop features to move elements into different positions. This type of presentation is also great for engagement. 
• Data visualizations : These types of visuals are focused on numerical data, using charts, graphs, and diagrams to highlight key insights and trends.
• Videos and animations : These elements are often used to make difficult concepts easier to understand through elements like motion graphics or storytelling.

The importance of visuals in presentations

Visuals are a powerful component of any presentation, greatly enhancing the delivery of information. According to research by Prezi, the human brain processes visuals 60,000 times faster than text. The study also found that presentations with images, charts and other graphics are 43% more likely to be persuasive than those relying solely on text.

Beyond just conveying information, visual presentations help keep the audience engaged and improve their ability to remember key points. Studies also show that using visual aids triggers multiple areas of the brain, boosting both understanding and memory retention. This is particularly beneficial for the 65% of the population who are visual learners .

Key findings include:

• People remember 80% of what they see and do , but only 20% of what they read .
• Visual presentations increase audience engagement by 40% , making them more likely to respond and act on the message.

Creating an eye catching visual presentation isn’t just about aesthetics—it’s about effectively communicating your message in a way that sticks with your audience.

Types of visual aids used in presentation

Different visual aids are used for various contents and types of presentation formats. A good selection of visual aids can make a world of difference in a presentation, from clarifying complex information, infusing an added emotional dimension, or rendering abstract ideas more concrete. So, what are visual aids? To help you understand, here are some that are widely used for presentations: 

High-quality images help explain ideas or evoke emotions, offering context or improving storytelling in a presentation. For example, in educational presentations, images of historical events or scientific concepts provide context and clarity. In business settings, images are used to evoke emotions or reinforce brand identity, such as including images of products, teams, or customer testimonials.

Example : A history teacher lecturing on World War II might use real, historical photos to drive home the topic for the students, offering them a concrete link with the events. 

2. Graphs and charts

Graphs and charts, such as bar graphs, pie charts, or scatter plots, present data in an easily digestible format. They’re perfect for comparing statistics, showing trends, or highlighting key points. These are especially useful when presenting data-heavy topics like quarterly sales performance, project progress, or scientific findings.

Example : A business leader presenting quarterly earnings might use a bar chart to compare revenue across different departments, helping the audience quickly grasp performance differences. While in scientific presentations, scatter plots can show correlations between variables, such as age and health outcomes, making abstract data more accessible and understandable.

3. Videos and animations

Videos can be used to visually explain processes or show testimonials or real-world applications. On the other hand, animations can be used to help explain complex processes or illustrate abstract concepts. This form of visual aid is very effective in training, product demos, and educational set-ups.

Example : In a corporate training session on new software, the program may be well illustrated by a short video that shows how to use it effectively, providing the participants with an enhanced perception of the interface. Likewise, in a medical presentation, an animated explainer video can show in visual detail a complex surgical procedure or how new medical equipment functions.

4. Infographics

Infographics are a blend of text and graphics and are found highly effective in summarizing and displaying vast amounts of data in a very presentable way. Such as overviews, comparison data or step-by-step processes. They enable the audience to read a lot of data quickly. 

Example : A presenter talking about climate change may bring in an infographic to summarize and give the key statistics related to worldwide temperature increases, CO2 emissions, and effects on ecosystems. This method makes very technical data readily comprehensible at first glance, especially in statistic-heavy presentations.

5. Text and quotes

Though text should be used sparingly for presentations, it can be used in visuals to drive home a point with some memorable quotes or key takeaways. It shouldn’t overshadow the message conveyed by the graphics or duplicate them, but provide an underscore of what’s being displayed visually.

Example : During a leadership presentation, a presenter might conclude by reiterating an inspirational quote from a well-known leader. Alternatively, during a sales pitch, a bold key statistic placed next to a product image can drive home the effect or benefits of what’s being discussed and reinforce the verbal message.

It’s important to pick the right kind of visuals for your presentation so that what you’re communicating is well received by the audience. They help simplify any complex ideas and help the message stick. From displaying data trends with graphs or using videos to enliven real-life examples, including appropriate visual components will further drive home your message during the presentation.

What is also known as a visual aid in a presentation?

There’s another common visual aid that often gets overlooked when it comes to visual presentations: 

Props are physical objects used to make content more tangible by providing a real-world example of what’s being talked about. They can help the audience follow or retain any points being made in the presentation.

Example : In a product demo presentation, a speaker might use the actual product as a prop to demonstrate its features and benefits. For example, a technology company could showcase the latest smartphone model, physically showing its unique features while explaining its capabilities. Similarly, a teacher demonstrating a science experiment could use lab equipment as props to visually support the steps of the process.

Props are particularly effective in fields such as education, product development, and sales, where tangible objects help bridge the gap between theory and practice.

Visual presentation examples

Here are some visual presentation ideas from Prezi that demonstrate how to effectively use visuals to create engaging and memorable presentations:

1. Why Leaders Need to Get Out of Their Own Way

This visual presentation highlights leadership challenges and personal barriers that leaders often face. It uses Prezi’s zooming and panning features to focus on key points, making the content both dynamic and accessible.

2. How to Be More Productive and Focus

This visual presentation combines data visualizations and clean design to provide practical tips on improving productivity. The use of visuals helps break down time management techniques, making the content more digestible for the audience.

3. U.S. Census: Why We Do It

This visual presentation showcases the U.S. Census, explaining its purpose and importance through strong visual elements such as infographics, charts, and historical images.

4. Creative Report

A perfect example of how to present creative concepts, this visual presentation uses interactive elements and multimedia to explore the power of creativity in communication.

5. Imposter Syndrome or Incompetence

This visual presentation discusses the psychological challenges of imposter syndrome using visual storytelling. The clear layout and zoomable sections guide the audience through the topic step-by-step.

Dos and don’ts of visual presentations

Creating a successful visual presentation requires balance. Here are some essential dos and don’ts to help you design an effective and engaging visual presentation.

Do: Use high-quality visuals

Be sure to include images, graphics, and videos that are relevant to your content. A clear message should not be easily distracted by an unclear picture.

Don’t: Overload with text

Avoid cramming too much text onto your slides. Visual presentations should rely more on images and graphics, with minimal text for emphasis.

Do: Keep it simple

Visual presentations shouldn’t contain too much information. Emphasize one idea per slide or section to prevent the audience from being overwhelmed.

Don’t: Clutter slides with unnecessary visuals

Don’t use visuals just for the sake of filling space. Every visual element should serve a purpose and support your key message.

Do: Add some interactivity

Make it interesting for the audience with some clickable parts and zoomable slides which you can create in Prezi.

Don’t: Use too many animations

While animations can add flair, overusing them can make your presentation feel chaotic. Stick to purposeful animations that enhance your content.

Do: Use consistent branding

Ensure uniform branding is used throughout. Use the same fonts, colors, and design elements. It not only looks professional but also drives brand identity home.

Don’t: Ignore the flow

Ensure your presentation has a logical flow. Disorganized content, even with strong visuals, can confuse your audience.

Do: Create a story

Apply storytelling methods to walk the audience through the presentation. This makes it more personal and easier to remember.

Don’t: Forget about accessibility

Ensure your visuals and text are accessible to everyone, including those with visual impairments. Use readable fonts and provide text descriptions for important images or graphs.

How do you give a visual presentation?

A good visual presentation isn’t only about making the presentation but also delivering it effectively. Here are some concrete steps to help you through organizing, creating, and delivering a strong visual aid presentation.

The creation process: organizing your visual presentation

Start with a clear outline.

Plan your content : Begin by outlining how the presentation is structured. What is the key message? What goal do you want your audience to take away? Break your content down into an introduction, some main points, and a conclusion. This will make the flow smooth and confirm that the message is clear and coherent. Highlight key takeaways : Zero in on 2–3 main points to emphasize and structure your visuals around these key ideas.

If you want to learn more on how to effectively structure any presentation, watch the following video here:

Choose the right visuals

Select impactful visuals : The choice of visuals underlines the whole success of a visual presentation, so choose them wisely. If you’re presenting data, then graphs or charts should be applied; for emotional impact or telling stories, use strong images or videos. They should complement your spoken message without overwhelming it.

Use high-quality visuals : Images, graphs or videos should be professional and high-resolution. Low-quality visuals can detract from your presentation.

Keep it consistent : Use a consistent design theme across your presentation, including fonts, colors, and style. This creates a polished, cohesive experience.

Use storytelling techniques

Weave a narrative : Presentations are easily remembered if told as a story . Be it a business update, an explanation of a scientific concept, or a product pitch, the story must flow naturally from beginning to end. This emotionally connects the audience to what’s being presented.

Contextualize the data : Instead of just showing numbers or statistics, use storytelling to explain what the data means and why it matters. This can help engage your audience more deeply.

Leverage interactive features

Incorporate Prezi’s interactive elements : If using Prezi, make sure you take advantage of its dynamic zooming and panning by integrating as much interactivity as possible into the experience. With Prezi, you can look at topics in a nonlinear fashion by zooming in on important details and then zooming out to see how the idea fits into the bigger picture.

Interactive visuals : Add clickable elements to your presentation to make the audience feel involved. Prezi also offers various ways to create interactive slides, keeping the audience engaged throughout.

The presenting process: delivering your visual presentation

Practice your delivery.

Rehearse transitions : Practice your presentation with the visuals several times before the event. This helps ensure smooth transitions between visuals and spoken points, making the presentation feel polished and professional.

Synchronize with visuals : Make sure your verbal presentation matches the timing of your visuals. Each visual should correspond to each point being made, without taking away attention from your speech. If you’re moving from one image or graph to another, ensure that your narration coincides with these transitions.

Engage the audience

Ask questions : Encourage participation by asking open-ended questions throughout your presentation. This can help break up the content, invite discussion, and keep the audience attentive.

Use Prezi’s features for interaction : Take advantage of Prezi’s capabilities to invite the audience to explore different sections or points of interest, ensuring the presentation remains engaging.

Respond in real-time : Allow your audience to ask questions or provide feedback throughout the presentation, rather than waiting until the end. This makes the presentation feel more like a conversation and keeps energy levels high.

Maintain eye contact and body language

Confident body language : Keep your body language open and confident. Stand tall, use gestures to emphasize key points, and move around if the setting allows it. To learn more about body language, watch the following video:

Eye contact : Make frequent eye contact with your audience to establish a connection and build trust.

End with a strong conclusion

Recap key points : Finish by summarizing your key takeaways and reinforcing the most important points you’ve made. This helps the audience retain the information.

Call to action : If your presentation is designed to encourage a particular action—such as adopting a new business strategy, supporting a cause, or purchasing a product—end with a clear, actionable call to action.

Refine your content with Prezi AI

Use Prezi AI text editing : Prezi AI can offer suggestions to improve phrasing, ensuring your content is polished and refined.

AI-generated visuals : Prezi AI can suggest appropriate visuals for your presentation, guaranteeing the visual message complements that of the core content.

By breaking down the creation and presentation processes, you can deliver a strong visual presentation that effectively communicates your message, engages your audience, and leaves a lasting impression.

Leveraging Prezi for visual presentations

Prezi is a standout visual presentation tool because of its dynamic movement, interactive features, and robust AI-driven content creation . Slide-based presentations are built on the basis of one slide following another in a linear fashion; but Prezi’s format liberates presenters to zoom in and out during the presentation, which makes the journey far more interesting for the audience. From sharing complex data to telling a story, Prezi equips presenters with effective communication tools for any type of content.

Dynamic movement and zooming

A core feature that makes Prezi unique is its seamless panning and zooming within the presentation. Users can move freely between different parts of their work, which creates a far less linear, rigid structure than typical static slideshows.

For example, if you’re delivering a presentation on leadership styles , you could zoom into individual leadership types, giving the audience an in-depth look at each one, before zooming out to provide a broader comparison. This movement keeps the audience engaged, as it visually mirrors the mental shift between different sections or ideas. It’s perfect for presentations that need to show relationships between various elements or provide a top-down understanding of complex topics.

Prezi AI: Your time-saving, creative partner

Prezi AI takes the creation process to a whole new level. It not only refines your content but also helps you craft an engaging and visually stunning presentation in minutes. Here are some of the benefits of using Prezi AI: 

AI-powered text editing

Prezi AI doesn’t just assist in generating content; it actively helps you refine it. Whether you need to polish your language, improve clarity, or adjust tone, the Prezi AI text editing tool provides smart suggestions to make your content more impactful.

Turning bullet points into animated slides

What makes Prezi AI unique is its capability to take basic bullet points and make them into fully dynamic and animated slides. This feature reduces the time you spend designing each slide and increases the time that can be put into refining your message. With a click, Prezi AI lays out content in visually interesting ways to keep your audience focused on what’s important. Start with a basic list of ideas and let Prezi AI convert them into an animated story that transitions smoothly from one point to the next.

Smart content suggestions

Prezi AI has the ability to suggest appropriate visuals and layouts while taking into account what your presentation is about. For example, in a storytelling presentations, Prezi AI may bring out the visual imagery that fits into telling the story well. This not only saves time but makes the presentation uniform in appearance for easy comprehension.

Streamlining the design process

With Prezi AI, you don’t need to be a design expert to create a professional-looking presentation. The AI automatically selects color schemes, fonts, and layouts that match your content, allowing you to deliver a visually cohesive presentation. It removes the guesswork from design, ensuring that your presentation not only looks polished but also aligns with your brand or theme.

Prezi templates: Customizable and designed for impact

What makes Prezi’s templates really good is how flexible they are. Be it a presentation on leadership or one that displays data or stories, Prezi has pre-built templates for your needs.

For example, Prezi offers finance templates that make it easy to present complex numbers or trends without overwhelming your audience. On the other hand, if you’re working on a more narrative-driven presentation, Prezi’s education templates allow you to seamlessly guide your audience through a journey. And the best part? These templates aren’t static; they’re highly customizable, allowing you to tweak them to fit your brand, message, and style.

Why Prezi AI makes visual presentations easier and better

Prezi AI is more than a simple design tool—it helps you elevate your presentations without added effort. From suggesting the best visuals to refining your content with AI text editing, Prezi AI ensures your presentation is polished, engaging, and impactful.

Prezi AI simplifies the creation process by handling the heavy lifting, allowing you to focus on delivering a presentation that resonates with your audience. Whether you’re presenting complex data, explaining a detailed process, or sharing a narrative, Prezi’s AI capabilities ensure your message comes through clearly and memorably.

Use Prezi to make your next visual presentation stand out from the crowd

Creating an effective visual presentation isn’t just about adding images on slides. It’s about careful planning, choosing the right visuals, and enthralling the audience with dynamic stories. Prezi simplifies this process by offering editable templates with AI-driven features and interactivity that enlivens your presentation.

Whether it’s a data presentation, storytelling, or explaining difficult concepts, Prezi features will make your visual presentation eye-catching for the viewer. For more ideas and inspiration on creating visual presentations, explore our guide on presentation styles and enhance your presentation skills today!

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SGS Scholar's Toolkit via Zoom

Do you want to turn your data into a compelling story that captures your audience's attention? Join us for a Zoom presentation to learn the critical skill of data visualization with  Jess Cohen-Tanugi , Visualization Specialist at Harvard Library.

Series: SGS Scholar's Toolkit

Title: Best Practices for Data Visualization

Date: Friday, October 25

Time: 12-1 pm

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