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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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Present Your Data Like a Pro

• Joel Schwartzberg

Demystify the numbers. Your audience will thank you.

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.

• JS Joel Schwartzberg oversees executive communications for a major national nonprofit, is a professional presentation coach, and is the author of Get to the Point! Sharpen Your Message and Make Your Words Matter and The Language of Leadership: How to Engage and Inspire Your Team . You can find him on LinkedIn and X. TheJoelTruth

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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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• Presentations

How to Present Data & Numbers in Presentations (Like a Pro)

Data is more important than ever. But do you know how to present data? Your audience needs information in a way that's easy-to-follow. With charts and graphs, data comes to life.

In this tutorial, you'll learn how to present data. The intuitive presentation of data and information is essential so that your point comes across. With our tips, we'll help you take flat data tables and convert them to useful and explanatory charts.

Why Present Data and Numbers With Charts?

Often, you’ll find yourself presenting data in PowerPoint. It’s a useful tool to illustrate data and bring numbers to life. But if you go about it the wrong way, you’ll distract and confuse your audience. Remember, the goal of sharing data is to deliver insights.

When you think of how to present data, you've got several options. Words alone should be an automatic no-no. Clustering numerical data in text paragraphs will confuse an audience. Similarly, tables don’t go far enough.

Consider the example below. While this approach may work for a simple dataset, it’s hard to capture value insights at a glance. Keep in mind, you want a viewer to quickly grasp the fundamental meaning of the data instantly.

That’s why your best option is to present data and numbers with charts. These are two related ways to present data that take a truly visual approach. Charts and graphs are forms of infographics. An infographic is a visual illustration meant to show ideas. They look great, they're easy to read, and they work.

Recent research vividly shows their effectiveness. Infographics are read at a rate of 30:1 over text articles. Pair this with the fact that visual information represents 90% of what transmits to a reader’s brain . Clearly, these are tools to keep in your wheelhouse.

As you can see below, the table data above transforms from a complex table to a clear and concise visual. It’s the identical range of data! The magic happens in the display of it. Charts are the key to success in the presentation of data and information.

How to Present Data and Numbers in Presentations

We’ve learned that the best way to present data is with charts. Now that you’re armed with this knowledge, you've got many options to choose from.

Premium PowerPoint data presentation templates are your best friend. These take the hard work out of building and sharing data charts. They teach you how to present data in presentations with pre-built options. All you need is your dataset!

For our walkthrough tutorial, we’ll use the Chart Presentation template from Envato Elements. It’s a premium option with 24 custom slide designs inside. Each is easy to customize to meet your data presentation needs.

With the template downloaded and opened in PowerPoint, let’s get to work learning how to present data. Follow the principles below, and you’ll be ready to get started!

1. Assess Your Data

Charts come in all shapes and sizes. There are pie charts, column charts, line charts, and many more. All have many uses, but each is targeted towards different types of data. First, you’ll want to assess the data that you have, and how it would best be presented visually. Let’s work with a sample dataset like the one below.

As you can see, the data has several rows, each representing a different country. Beside these are three columns, each covering sales for a given year. In short, you’re looking at three years of sales forecasts for five countries.

Reading over the data, it’s tough to instantly gain any insights. Sure, if you look long enough, trends start to emerge. But this is a slow, manual process. And imagine if there were fifty countries and twelve years, for example!

Manual analysis would become nearly impossible in a presentation setting. But by using a chart, you can instantly illustrate trends and forecasts. Any viewer – even an untrained eye – can readily see all key points with a moment’s glance.

2. Choose a Visual

Now that you’ve analyzed your data, you can easily see that a chart is essential. But what kind? We briefly mentioned three styles of charts. When you think of how to present data in presentation form, the trick is to choose the style that best fits your data.

For our example, we’re looking at multiple data points for several categories. Here, these data points are three sales values, for five countries each. Keep these ideas for how to present numbers in mind:

• A logical visual would group each country together.
• Then, show each of the three sales figures side by side.
• You could also reverse it – group the years and show sales for all five countries.

In a case like this, a column chart is the ideal choice. These group data just as described.

But when might a different chart type be useful? Imagine if your data included details about Germany’s 2024 sales, for example. Suppose you’re presenting to your marketing team, and they’ve asked how sales of each individual product make up the total. Here, a pie chart would be the perfect option. These show how individual pieces form a whole.

But in this case, we’ve decided on a column chart. Find one in the deck, and let’s insert it. In our template, slide #15 contains a beautiful chart. It’s already built. All you need to do is add your own data.

To do that, click into the chart area, then right-click. From the menu, choose Edit Data. You’ll see an embedded Microsoft Excel spreadsheet launch right inside of PowerPoint. From here, you can simply replace the existing data with the table you already have. As you work, the chart instantly updates itself to match the new data.

In moments, you’ll be presenting data in PowerPoint with this beautiful chart!

3. Style Your Visual

With your chart placed on the slide, you now have an array of design options. Remember, the goal is to make the chart work perfectly for your own data. These options primarily live on the Chart Design menu, which you can find on PowerPoint’s ribbon. With the chart selected, click on Chart Design.

The template has a beautiful color palette, but you can add your own. It helps to choose a color profile with plenty of contrast. This makes your visual even clearer and easier to read.

To add a new palette, click on the Change Colors drop-down menu. You’ll see an array of color swatches display. Click on one, and it'll apply to your chart.

You can add a new background by launching the Chart Styles section in the center of the Chart Design menu. For example, you can choose one with a gray background to make the colors really stand out on the slide.

Also, it’s possible to add more context to the data. The horizontal axis in our example is clear enough, listing countries. But there isn’t any explanation of what the vertical axis represents, or the colorful bars. Follow these steps:

• Open the Add Chart Element dropdown near the upper left of the ribbon.
• Click  Axis Titles.
• Choose Primary Vertical.
• You’ll see Axis Title appear on the chart. This is a text box, which you can select and type into.

Finally, back on the Add Chart Element dropdown, choose Legend , and pick a location like Top . Three colorful squares listing the three years shown in the chart will be added to the drawing. These labels aid in the presentation of data and information.

It’s easy to see how to present numbers in chart form, using PowerPoint. Start with a premium template like this, and then customize the chart inside to fit your needs.

4. Add Notes Where Needed

You now know well that charts are the best way to present data. But they don’t have to stand on their own!

Often, it’s useful to add more context. Audiences may understand the data perfectly but have questions. For example: Why are sales for one country climbing, while they are falling in another?

By adding notes where needed, you can add supporting details. It’s best to keep these off of the chart itself. If you clutter up your visual, the value of it diminishes rapidly. Check out an improved example below.

On our slide example, the paragraph section on the left may become a series of quick bullet points. These add supporting details that more fully explain the data shown in the chart.

Again, you may not always need to do this. But never think that a chart must be all-encompassing, explaining every piece of information by itself. The trick is to boost understanding, while remaining clear and concise.

5. Consider an Appendix

You may have extra details that you need to include in your slides.

In our example, imagine that you've got three sales offices in each of the five countries featured. Each of the fifteen makes up a certain percentage of overall sales. This may be key data for your audience, but it would complicate the visual that you just created.

Here, it’s a good idea to add an appendix. An appendix (often at the end of your slide deck) includes more detailed data. You might not review it with a live audience, but they can look at it later in a handout or digital format.

To add an appendix, go to the end of your presentation, and click New Slide on the Home tab. Here, it might be appropriate to share the detailed data in the form of a table. Or, you can add a pie chart, suitable for this style of dataset.

To add a chart from scratch, go to the Insert tab, then choose Chart > Pie. The embedded Excel window will return, and again, you can insert your data.

An appendix may not always be necessary. But you should include one (or more) if you've got meaningful data that you aren’t placing into the main slide deck.

The Best Source for Data Presentation Templates (With Unlimited Downloads)

Envato Elements is the best place to find top data presentation templates . For a low monthly rate, you've got access to unlimited downloads of PPT chart templates. You can try as many as you want, finding those that work best for you.

Explore PowerPoint Chart Templates

And that isn’t all. As an Elements member, you also have unlimited access to stock photos, music, fonts, and more. These are digital assets that pair perfectly with your data presentation.

Elements is an unbeatable offer because of the unlimited flexibility. With premium templates, you gain access to powerful features not found in free designs:

• beautiful data visuals that are pre-built and ready to customize
• stylish, custom fonts to help text stand out
• media placeholders to add supporting images and videos
• fully flexible layouts that adapt to your data and other content

The advantages are many. You save hard work, by leaving the slide design tasks to experts. This gives you the time needed to refine your message. Plus, the finished product will wow any audience, thanks to the expertly-crafted graphics . Truly, Envato Elements is the best value for creatives today.

Need a template, but don't want an unlimited subscription? We've got you covered with templates from GraphicRiver . You'll pay-as-you-go, and these templates give you everything you need. They've got pre-made designs for the best way to present data with less work than ever before.

Now Practice the Best Way to Present Data in Presentations

You just learned new ways to present data. Essentially, you saw how to present data in presentations so that your audience  can understand it. Great presenters think of the audience first. They'll thank you for your thoughtful work in how to present numbers and more.

Now, it's your turn! Put these tips on how to present data in presentations to work. Take a flat table in a presentation and convert it with our tips for presenting data in PowerPoint. Just download a template and get started. 

Mastering the Art of Presenting Data in PowerPoint

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

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

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

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

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

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

Creative ways to present data in powerpoint.

• Tips for data visualization

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

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

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

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

1. Collect your data

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

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

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

2. Know your audience

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

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

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

3. Choose a data visualization option

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

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

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

4. Be creative!

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

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

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

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

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

Line Charts

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

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

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

Download our Free Line Chart Template here .

Bar and column charts

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

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

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

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

Download our Bar and Column Chart Template here .

Venn diagram

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

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

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

Download our Free Venn Diagram Template here .

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

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

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

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

Download our Free Pie Chart Template here .

Bubble Charts

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

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

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

Download our Free Bubble Chart Template here .

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

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

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

Download our Free World Map Template here .

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

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

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

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

Download our Free Timeline Chart Template here .

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

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

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

Download our Free Flowchart Template here .

5 Tips for data visualization in PowerPoint

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

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

1. Keep it simple

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

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

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

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

2. Be original

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

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

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

3. Focus on your brand

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

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

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

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

4. Highlight key information

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

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

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

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

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

5. Use Templates!

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

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

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

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

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

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

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

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

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

Boost your team’s productivity with the 24Slides Pro Plan , which includes a 10-hour turnaround, dedicated support, and special rates. Explore Pro now!

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

• 20+ Free PowerPoint and Google Slides Templates for Data Presentations
• PowerPoint 101: The Ultimate Guide for Beginners
• How to Create the Perfect B2B Sales Presentation
• 7 Essential Storytelling Techniques for Your Business Presentation
• The Cost of PowerPoint Presentations: Discover the hidden expenses you might overlook!

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Data Presentation Techniques that Make an Impact

Create beautiful charts & infographics get started, 10.05.2016 by anete ezera.

Presenting data doesn’t need to be boring. In fact, it is a great way to spice up your presentations and share important facts and figures with your audience. Data has the power to be engaging, persuasive and memorable.

If you have a compelling story to tell with data, you should present it in a clear and powerful way. We will help you get started with a few effective data presentation techniques!

If you’d like more information about designing great presentations, download our new eBook ‘How to Design PowerPoint Presentations that Pack a Punch in 5 Easy Steps.’

What Presentations Benefit from Data?

Data doesn’t necessarily make all presentations better, but certain types of presentations are prime for the incorporation of data visualizations:

• Sales Reports
• PR and Marketing Research
• Marketing and Advertising Campaigns
• Executive and CEO Presentations
• Educational Reports
• Political Speeches
• Annual Reports
• Shareholder Presentations
• Financial Reports
• Product Launches, and more!

Why Use Charts in Presentations?

Visuals make information stick in our brains . A study from the Wharton School of Business found that 67% of the audience surveyed were persuaded by verbal presentations that had accompanying visuals. Charts are great visual aids for multiple reasons:

• Charts are easy to read
• Charts are visually appealing
• Charts simplify complex information
• Charts make it possible to quickly make comparisons and spot trends
• Charts are memorable and make an impact
• Charts give your presentation credibility

How to Add Data to Your Presentation

1) define your message.

Before you can even think about adding data to your presentation, you need to ask yourself, ‘what story am I trying to tell?’ Once you have a concrete idea of what your message is, you’ll have an easier time crafting the right visualization to share with your audience.

2) Clean and Organize Your Data

Now that you know what point you want to make with your data, it’s time to make sure your numbers are ready to be visualized.   Every good data visualization starts with good data. Make sure your spreadsheet is formatted and labeled exactly how you want it. Think about the message you want to share with your data and get rid of anything that doesn’t help you tell your story.

Data that is clean and organized is easier to display and analyze. Here are five awesome free data analysis tools to help you extract, clean, and share your data.

3) Pick the Right Chart Type

We can’t emphasize enough how important it is to make sure you pick the right chart type for the data you want to present. While your data might technically work with multiple chart types, you need to pick the one that ensures your message is clear, accurate, and concise.

4) Simplicity is Key

Charts and graphs turn complex ideas or data sets into easy-to-understand visual concepts. Remember that your data is the star of the show, so keep it simple. Avoid visual clutter, excessive text, poor color selection, and unnecessary animations. Make sure your legend and data labels are printed in a large, visible font. You don’t want your audience to get distracted. Less is more!

5) Create a Narrative

People understand stories better than they understand spreadsheets. Craft a compelling story around your data to make it memorable. Find a way to drive emotion from the numbers. Give your audience something they can relate to and resonate with. Data visualization speaker Bill Shander offers five tips to make you a better data storyteller. 

6) Visualize Data with Infogram

Before you add data to your presentation you need to visualize it. While many presentation tools allow you to create charts , they often leave much to be desired. Infogram makes it easy to create beautiful, engaging data visualizations your audience won’t forget.

You can embed interactive and responsive data visualizations into your presentations if you’re using Bunkr or any other HTML based presentation platform. Or, if you upgrade to one of our paid plans , you can download static versions of your charts and graphs to enhance your work. You can even make the background of PNG downloads transparent so they slip seamlessly into your presentation.

Would you like to experience the full power of  data visualization ? Try Infogram for Teams or Enterprise for free! With a Team or Enterprise account, you can create up to 10,000+ projects, collaborate with your team in real time, use our engagement analytics feature, and more. Request your free demo  here .

7) Make a Handout

Leave your audience with a physical or virtual copy of your charts. This makes it possible for them to look at the numbers more closely after your presentation. It’s also nice to include extra information, beyond what you covered, in case someone wants to delve deeper into the material.

Now that you know how to add data to your presentations, it’s time to learn how to design a PowerPoint that really gets people talking. Download our latest eBook ‘How to Design PowerPoint Presentations that Pack a Punch in 5 Easy Steps’ – for free!

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Infogram improved accessibility with wcag 2.2 compliance, how to write alt text descriptions: a comprehensive guide, how to create accessible charts and graphs with infogram.

10 Superb Data Presentation Examples To Learn From

The best way to learn how to present data effectively is to see data presentation examples from the professionals in the field.

We collected superb examples of graphical presentation and visualization of data in statistics, research, sales, marketing, business management, and other areas.

On this page:

How to present data effectively? Clever tips.

• 10 Real-life examples of data presentation with interpretation.

Download the above infographic in PDF

Your audience should be able to walk through the graphs and visualizations easily while enjoy and respond to the story.

[bctt tweet=”Your reports and graphical presentations should not just deliver statistics, numbers, and data. Instead, they must tell a story, illustrate a situation, provide proofs, win arguments, and even change minds.” username=””]

Before going to data presentation examples let’s see some essential tips to help you build powerful data presentations.

1. Keep it simple and clear

The presentation should be focused on your key message and you need to illustrate it very briefly.

Graphs and charts should communicate your core message, not distract from it. A complicated and overloaded chart can distract and confuse. Eliminate anything repetitive or decorative.

2. Pick up the right visuals for the job

A vast number of types of graphs and charts are available at your disposal – pie charts, line and bar graphs, scatter plot , Venn diagram , etc.

Choosing the right type of chart can be a tricky business. Practically, the choice depends on 2 major things: on the kind of analysis you want to present and on the data types you have.

Commonly, when we aim to facilitate a comparison, we use a bar chart or radar chart. When we want to show trends over time, we use a line chart or an area chart and etc.

3. Break the complex concepts into multiple graphics

It’s can be very hard for a public to understand a complicated graphical visualization. Don’t present it as a huge amount of visual data.

Instead, break the graphics into pieces and illustrate how each piece corresponds to the previous one.

4. Carefully choose the colors

Colors provoke different emotions and associations that affect the way your brand or story is perceived. Sometimes color choices can make or break your visuals.

It is no need to be a designer to make the right color selections. Some golden rules are to stick to 3 or 4 colors avoiding full-on rainbow look and to borrow ideas from relevant chart designs.

Another tip is to consider the brand attributes and your audience profile. You will see appropriate color use in the below data presentation examples.

5. Don’t leave a lot of room for words

The key point in graphical data presentation is to tell the story using visuals and images, not words. Give your audience visual facts, not text.

However, that doesn’t mean words have no importance.

A great advice here is to think that every letter is critical, and there’s no room for wasted and empty words. Also, don’t create generic titles and headlines, build them around the core message.

6. Use good templates and software tools

Building data presentation with AI nowadays means using some kind of software programs and templates. There are many available options – from free graphing software solutions to advanced data visualization tools.

Choosing a good software gives you the power to create good and high-quality visualizations. Make sure you are using templates that provides characteristics like colors, fonts, and chart styles.

A small investment of time to research the software options prevents a large loss of productivity and efficiency at the end.

10 Superb data presentation examples 

Here we collected some of the best examples of data presentation made by one of the biggest names in the graphical data visualization software and information research.

These brands put a lot of money and efforts to investigate how professional graphs and charts should look.

1. Sales Stage History  Funnel Chart 

Data is beautiful and this sales stage funnel chart by Zoho Reports prove this. The above funnel chart represents the different stages in a sales process (Qualification, Need Analysis, Initial Offer, etc.) and shows the potential revenue for each stage for the last and this quarter.

The potential revenue for each sales stage is displayed by a different color and sized according to the amount. The chart is very colorful, eye-catching, and intriguing.

2. Facebook Ads Data Presentation Examples

These are other data presentation examples from Zoho Reports. The first one is a stacked bar chart that displays the impressions breakdown by months and types of Facebook campaigns.

Impressions are one of the vital KPI examples in digital marketing intelligence and business. The first graph is designed to help you compare and notice sharp differences at the Facebook campaigns that have the most influence on impression movements.

The second one is an area chart that shows the changes in the costs for the same Facebook campaigns over the months.

The 2 examples illustrate how multiple and complicated data can be presented clearly and simply in a visually appealing way.

3. Sales Opportunity Data Presentation

These two bar charts (stacked and horizontal bar charts) by Microsoft Power Bi are created to track sales opportunities and revenue by region and sales stage.

The stacked bar graph shows the revenue probability in percentage determined by the current sales stage (Lead, Quality, Solution…) over the months. The horizontal bar chart represents the size of the sales opportunity (Small, Medium, Large) according to regions (East, Central, West).

Both graphs are impressive ways for a sales manager to introduce the upcoming opportunity to C-level managers and stakeholders. The color combination is rich but easy to digest.

4. Power 100 Data Visualization 

Want to show hierarchical data? Treemaps can be perfect for the job. This is a stunning treemap example by Infogram.com that shows you who are the most influential industries. As you see the Government is on the top.

This treemap is a very compact and space-efficient visualization option for presenting hierarchies, that gives you a quick overview of the structure of the most powerful industries.

So beautiful way to compare the proportions between things via their area size.

When it comes to best research data presentation examples in statistics, Nielsen information company is an undoubted leader. The above professional looking line graph by Nielsen represent the slowing alcoholic grow of 4 alcohol categories (Beer, Wine, Spirits, CPG) for the period of 12 months.

The chart is an ideal example of a data visualization that incorporates all the necessary elements of an effective and engaging graph. It uses color to let you easily differentiate trends and allows you to get a global sense of the data. Additionally, it is incredibly simple to understand.

6. Digital Health Research Data Visualization Example

Digital health is a very hot topic nowadays and this stunning donut chart by IQVIA shows the proportion of different mobile health apps by therapy area (Mental Health, Diabetes, Kidney Disease, and etc.). 100% = 1749 unique apps.

This is a wonderful example of research data presentation that provides evidence of Digital Health’s accelerating innovation and app expansion.

Besides good-looking, this donut chart is very space-efficient because the blank space inside it is used to display information too.

7. Disease Research Data Visualization Examples

Presenting relationships among different variables is hard to understand and confusing -especially when there is a huge number of them. But using the appropriate visuals and colors, the IQVIA did a great job simplifying this data into a clear and digestible format.

The above stacked bar charts by IQVIA represents the distribution of oncology medicine spendings by years and product segments (Protected Brand Price, Protected Brand Volume, New Brands, etc.).

The chart allows you to clearly see the changes in spendings and where they occurred – a great example of telling a deeper story in a simple way.

8. Textual and Qualitative Data Presentation Example

When it comes to easy to understand and good looking textual and qualitative data visualization, pyramid graph has a top place. To know what is qualitative data see our post quantitative vs qualitative data .

9. Product Metrics Graph Example

If you are searching for excel data presentation examples, this stylish template from Smartsheet can give you good ideas for professional looking design.

The above stacked bar chart represents product revenue breakdown by months and product items. It reveals patterns and trends over the first half of the year that can be a good basis for data-driven decision-making .

10. Supply Chain Data Visualization Example 

This bar chart created by ClicData  is an excellent example of how trends over time can be effectively and professionally communicated through the use of well-presented visualization.

It shows the dynamics of pricing through the months based on units sold, units shipped, and current inventory. This type of graph pack a whole lot of information into a simple visual. In addition, the chart is connected to real data and is fully interactive.

The above data presentation examples aim to help you learn how to present data effectively and professionally.

About The Author

Silvia Valcheva

Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI (Artificial Intelligence), IoT (Internet of Things), process automation, etc.

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• Interactive Presentation

10 Methods of Data Presentation That Really Work in 2024

Leah Nguyen • 20 August, 2024 • 13 min read

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

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

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

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Data Presentation - What Is It?

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

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

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

Good data presentation helps…

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

Methods of Data Presentation and Examples

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

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

#1 - Tabular 

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

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

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

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

(Source: CustomerThermometer )

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

#3 - Pie chart

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

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

#4 - Bar chart

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

They can be as simple as this:

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

#5 - Histogram

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

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

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

#6 - Line graph

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

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

#7 - Pictogram graph

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

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

#8 - Radar chart

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

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

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

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

#9 - Heat map

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

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

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

#10 - Scatter plot

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

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

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

5 Data Presentation Mistakes to Avoid

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

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

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

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

#2 - Use the wrong type of chart

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

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

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

#3 - Make it 3D

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

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

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

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

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

#5 - Bombard the audience with too much information

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

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

What are the Best Methods of Data Presentation?

Finally, which is the best way to present data?

The answer is…

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

For example:

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

Frequently Asked Questions

What is a chart presentation.

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

When can I use charts for the presentation?

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

Why should you use charts for presentation?

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

What are the 4 graphical methods of presenting data?

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

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A Guide to Effective Data Presentation

Key objectives of data presentation, charts and graphs for great visuals, storytelling with data, visuals, and text, audiences and data presentation, the main idea in data presentation, storyboarding and data presentation, additional resources, data presentation.

Tools for effective data presentation

Financial analysts are required to present their findings in a neat, clear, and straightforward manner. They spend most of their time working with spreadsheets in MS Excel, building financial models , and crunching numbers. These models and calculations can be pretty extensive and complex and may only be understood by the analyst who created them. Effective data presentation skills are critical for being a world-class financial analyst .

It is the analyst’s job to effectively communicate the output to the target audience, such as the management team or a company’s external investors. This requires focusing on the main points, facts, insights, and recommendations that will prompt the necessary action from the audience.

One challenge is making intricate and elaborate work easy to comprehend through great visuals and dashboards. For example, tables, graphs, and charts are tools that an analyst can use to their advantage to give deeper meaning to a company’s financial information. These tools organize relevant numbers that are rather dull and give life and story to them.

Here are some key objectives to think about when presenting financial analysis:

• Visual communication
• Audience and context
• Charts, graphs, and images
• Focus on important points
• Design principles
• Storytelling
• Persuasiveness

For a breakdown of these objectives, check out Excel Dashboards & Data Visualization course to help you become a world-class financial analyst.

Charts and graphs make any financial analysis readable, easy to follow, and provide great data presentation. They are often included in the financial model’s output, which is essential for the key decision-makers in a company.

The decision-makers comprise executives and managers who usually won’t have enough time to synthesize and interpret data on their own to make sound business decisions. Therefore, it is the job of the analyst to enhance the decision-making process and help guide the executives and managers to create value for the company.

When an analyst uses charts, it is necessary to be aware of what good charts and bad charts look like and how to avoid the latter when telling a story with data.

Examples of Good Charts

As for great visuals, you can quickly see what’s going on with the data presentation, saving you time for deciphering their actual meaning. More importantly, great visuals facilitate business decision-making because their goal is to provide persuasive, clear, and unambiguous numeric communication.

For reference, take a look at the example below that shows a dashboard, which includes a gauge chart for growth rates, a bar chart for the number of orders, an area chart for company revenues, and a line chart for EBITDA margins.

To learn the step-by-step process of creating these essential tools in MS Excel, watch our video course titled “ Excel Dashboard & Data Visualization .”  Aside from what is given in the example below, our course will also teach how you can use other tables and charts to make your financial analysis stand out professionally.

Learn how to build the graph above in our Dashboards Course !

Example of Poorly Crafted Charts

A bad chart, as seen below, will give the reader a difficult time to find the main takeaway of a report or presentation, because it contains too many colors, labels, and legends, and thus, will often look too busy. It also doesn’t help much if a chart, such as a pie chart, is displayed in 3D, as it skews the size and perceived value of the underlying data. A bad chart will be hard to follow and understand.

Aside from understanding the meaning of the numbers, a financial analyst must learn to combine numbers and language to craft an effective story. Relying only on data for a presentation may leave your audience finding it difficult to read, interpret, and analyze your data. You must do the work for them, and a good story will be easier to follow. It will help you arrive at the main points faster, rather than just solely presenting your report or live presentation with numbers.

The data can be in the form of revenues, expenses, profits, and cash flow. Simply adding notes, comments, and opinions to each line item will add an extra layer of insight, angle, and a new perspective to the report.

Furthermore, by combining data, visuals, and text, your audience will get a clear understanding of the current situation,  past events, and possible conclusions and recommendations that can be made for the future.

The simple diagram below shows the different categories of your audience.

  This chart is taken from our course on how to present data .

Internal Audience

An internal audience can either be the executives of the company or any employee who works in that company. For executives, the purpose of communicating a data-filled presentation is to give an update about a certain business activity such as a project or an initiative.

Another important purpose is to facilitate decision-making on managing the company’s operations, growing its core business, acquiring new markets and customers, investing in R&D, and other considerations. Knowing the relevant data and information beforehand will guide the decision-makers in making the right choices that will best position the company toward more success.

External Audience

An external audience can either be the company’s existing clients, where there are projects in progress, or new clients that the company wants to build a relationship with and win new business from. The other external audience is the general public, such as the company’s external shareholders and prospective investors of the company.

When it comes to winning new business, the analyst’s presentation will be more promotional and sales-oriented, whereas a project update will contain more specific information for the client, usually with lots of industry jargon.

Audiences for Live and Emailed Presentation

A live presentation contains more visuals and storytelling to connect more with the audience. It must be more precise and should get to the point faster and avoid long-winded speech or text because of limited time.

In contrast, an emailed presentation is expected to be read, so it will include more text. Just like a document or a book, it will include more detailed information, because its context will not be explained with a voice-over as in a live presentation.

When it comes to details, acronyms, and jargon in the presentation, these things depend on whether your audience are experts or not.

Every great presentation requires a clear “main idea”. It is the core purpose of the presentation and should be addressed clearly. Its significance should be highlighted and should cause the targeted audience to take some action on the matter.

An example of a serious and profound idea is given below.

To communicate this big idea, we have to come up with appropriate and effective visual displays to show both the good and bad things surrounding the idea. It should put emphasis and attention on the most important part, which is the critical cash balance and capital investment situation for next year. This is an important component of data presentation.

The storyboarding below is how an analyst would build the presentation based on the big idea. Once the issue or the main idea has been introduced, it will be followed by a demonstration of the positive aspects of the company’s performance, as well as the negative aspects, which are more important and will likely require more attention.

Various ideas will then be suggested to solve the negative issues. However, before choosing the best option, a comparison of the different outcomes of the suggested ideas will be performed. Finally, a recommendation will be made that centers around the optimal choice to address the imminent problem highlighted in the big idea.

This storyboard is taken from our course on how to present data .

To get to the final point (recommendation), a great deal of analysis has been performed, which includes the charts and graphs discussed earlier, to make the whole presentation easy to follow, convincing, and compelling for your audience.

CFI offers the Business Intelligence & Data Analyst (BIDA)® certification program for those looking to take their careers to the next level. To keep learning and developing your knowledge base, please explore the additional relevant resources below:

• Investment Banking Pitch Books
• Excel Dashboards
• Financial Modeling Guide
• Startup Pitch Book
• See all business intelligence resources
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• PRESENTATION SKILLS

Presenting Data

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When and how should you use data in a presentation?

The answer is that you should use figures and numbers whenever they give the best evidence to back up your argument, or to tell your story. But how to present that data is more difficult.

Many people are not interested in tables of numbers, and may struggle to understand graphs. How can you help walk them through the data?

This page is designed to help you to answer that question by setting out some simple rules for presenting data.

Remember that You Are Telling Your Audience a Story

All presentations are basically story-telling opportunities.

Human beings have been hard-wired, over millions of years of evolution, to enjoy and respond to stories. It’s best to work with it, not fight it, because if you tell your audience a story, they are likely to listen much more carefully, and also move towards a logical conclusion: the insight to which you are trying to lead them.

Once you understand this, the issue of using data falls into place: it is to provide evidence of how your story unfolds.

Use Data to Tell the Story

You are not presenting data as such, you are using data to help you to tell your story in a more meaningful way.

This means that whenever you are required to present data, you should be asking yourself:

‘ What is the story in this data? ’,

‘ How best can I tell this story to my audience? ’

A Picture Tells a Thousand Words

90% of the information sent to the brain is visual and over 90% of all human communication is visual. Processing text requires our brains to work much harder than when processing images. In fact, the brain can process pictorial information 60,000 times faster than written information.

There is considerable truth in the saying ‘a picture tells a thousand words’ . It may not be literally a thousand, but it is often much easier to use a picture than to describe numerical information in words.

The data itself may be vitally important, but without a visual presentation of that data, its impact (and therefore your message) may be lost.

There are many people in the world who do not find it easy to understand numbers.

There are also many people who will simply switch off if you show them figures in a table. But if you present data in a graph or pie chart, you make a pictorial representation of the data. It makes the numbers much easier to understand. Trends and proportions become more obvious.

Consider this set of data:

Even for the highly numerate, the immediate point is only that there are lot more sales in the first quarter. You would have to do some adding up and dividing to work out the relationships between the four numbers. It also requires much more concentration to read and absorb the information in this format.

Now consider the same data in a pie chart:

It is immediately and shiningly obvious, even for those who struggle with numbers, that more than half of all sales were in the first quarter, and that over 75% were in the first two quarters.

What’s more, nobody is going to be straining from the back of the room to read your figures. You really can see a lot more from a picture.

But, and this is important, make sure that the graph is a good one.

Check that your graph or chart is visually appealing, that all the labels are clear, and that you have used an appropriate type of graph or chart. Poor graph-making is always obvious and can lead to confusion. Your message will also have much more impact if you choose the right type of graph or chart.

For more about this, see our page on Graphs and Charts .

KISS: Keep It Simple, Stupid!

When you’re good at statistics, it’s very tempting to do some really whizzy analysis. And once you’ve done that, you really want to show everyone how clever you are, and how much work you’ve done.

But does it really help to make your point?

Then don’t present it.

In the (relatively rare) cases when you actually need some really whizzy analysis, you then need to ask yourself whether everyone will understand it. And, in these days of presentations being posted on the internet, will the casual reader of your slides understand it later?

Once again, if the answer is ‘probably not’, then don’t use it.

Leave It Out...

If you can’t summarise your analysis in one or two brief and clear sentences, then don’t include it.

It also follows that if you don’t need to include data to make your point, then it may be best not to do so. A slide that is likely to be misunderstood or produce confusion is worse than no slide at all. So cut out all unnecessary data and focus on what you really need  to tell your story .

Remember KISS: Keep It Simple, Stupid.

Highlight the Main Features to Draw Out the Insights

We’re not suggesting that you should ‘ dumb down ’ your presentation, but there is no harm in highlighting the key features, as well as cutting out unnecessary data.

Suppose once again that you are using the sales figures from the last four quarters. You want to show the actual figures. Why not use a highlighting tool to emphasise that the first quarter is more than half?

With PowerPoint and other presentation software, you can make each circle appear separately, as you make your point and discuss the insights.

A little creative use of the technology can help you to highlight certain figures, and once again, make the story clearer.

Take-home message

Paradoxically, your presentation of any data should be designed to move the conversation away from the data and into the insight and action that should result from it.

In other words:

‘What happened there?’

‘What are we going to do about it?’

If you look at your presentation, data and all, and it’s not clear how you would get from the data to the insight and then the action, it’s probably a good idea to look at it again.

Remember, it’s the story that matters… and then what happens as a result.

Continue to: Writing Your Presentation Working with Visual Aids

See also: What is Your Story? How to Identify Your Story from Raw Data Crisis Communications Presenting to Large Groups Simple Statistical Analysis

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

2. Column chart

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

3. Pie Charts

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

4. Bar charts

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

5. Histograms

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

6. Box plots

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

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

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

Importance of Data Presentation

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

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

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

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

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

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

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

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

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Express to impress: leveraging ibcs standards for powerful data presentations.

Posted on September 12, 2024 by Numbers around us in R bloggers | 0 Comments

Attention: Article looks long at word count, but remember that contains pretty long chunks of code.

Disclaimer: While my work in this series draws inspiration from the IBCS® standards, I am not a certified IBCS® analyst or consultant. The visualizations and interpretations presented here are my personal attempts to apply these principles and may not fully align with the official IBCS® standards. I greatly appreciate the insights and framework provided by IBCS® and aim to explore and learn from their approach through my own lens.

The Power of Expression in Data Reporting

In the world of business intelligence (BI) and data reporting, the ability to express data effectively can make or break the decision-making process. Amid an overwhelming flow of information, data must not only be analyzed but also communicated in a way that drives insight, action, and understanding. This is where the International Business Communication Standards (IBCS) framework comes into play, particularly its “Express” component within the SUCCESS acronym: Say, Unify, Condense, Check, Express, Simplify, Structure . The “Express” component is the critical bridge between data and comprehension, focusing on how data is visualized and presented.

At the heart of Express lies a simple question: How can we present data so that it is understood quickly and without misinterpretation? The answer is not just about using charts and tables but also about selecting the right types of visualizations that align with the information being conveyed. Leland Wilkinson’s Grammar of Graphics provides a theoretical backbone to this approach by laying out the essential building blocks of effective visual communication. Together, the principles from IBCS and the Grammar of Graphics guide us in transforming raw data into powerful visual narratives.

IBCS and the Grammar of Graphics: A Perfect Synergy

The IBCS framework emphasizes standardization and clarity in how information is visualized, calling for the replacement of ineffective chart types and encouraging the use of comparisons and explanatory visuals. This aligns well with Wilkinson’s Grammar of Graphics , which provides a systematic approach to visualizing data through a combination of geometric shapes, scales, and aesthetic properties. The Grammar of Graphics builds a foundation where every visual element — whether a point, line, or bar — serves a purpose and contributes to the clarity of the message.

These two frameworks together empower BI practitioners to not only present data but to express it in a way that makes patterns, comparisons, and insights obvious. This chapter will explore how the Express component of IBCS, complemented by the Grammar of Graphics , can turn confusing reports into clear, actionable data presentations.

Choosing the Right Object Types: Charts and Tables

One of the foundational elements of effective data presentation is selecting the correct type of visualization. According to the IBCS standards, charts and tables should be used strategically to express data in the clearest, most impactful way. Each chart type has its own strengths, and choosing the wrong one can lead to confusion, misinterpretation, or even worse, misleading conclusions. This section will focus on how to align chart types with IBCS guidelines and how the Grammar of Graphics can assist in structuring these visuals.

The Role of Appropriate Object Types

IBCS emphasizes simplicity and clarity, which translates into using visualization types that naturally align with the type of data you’re working with. The goal is to make the relationships, patterns, and insights in the data immediately apparent to the audience.

• Bar Charts : Bar charts are the workhorse of data visualization. They are ideal for showing comparisons, such as revenue across different regions or sales figures over several months. IBCS recommends horizontal bar charts to compare categories and vertical bar charts for time series data.
• Line Charts : Line charts excel at showing trends over time. In scenarios where you need to express changes, such as stock prices over a year or temperature changes, line charts are much more effective than other types like pie or radar charts.
• Tables : While charts help visualize data trends, tables are best suited for presenting precise numbers. IBCS guidelines advocate using tables when exact figures matter more than the visual trends, such as financial reports or performance metrics. A well-designed table that adheres to IBCS principles has a clear structure, avoids clutter, and presents data in a way that makes comparisons simple.

Transforming a Report with IBCS Principles

Let’s look at an example of transforming a poorly chosen chart type into a more effective IBCS-compliant visualization:

Before : Imagine a report that uses a pie chart to compare market share across different regions. While pie charts are common, they are not IBCS-compliant and make it difficult to compare exact proportions, especially when the differences are small.

After : By applying IBCS standards, we replace the pie chart with a horizontal bar chart . The bar chart not only allows for easier comparison of regions side by side but also makes it immediately clear which region has the largest or smallest market share. This simple change transforms the clarity and effectiveness of the report.

The Grammar of Graphics Approach

Leland Wilkinson’s Grammar of Graphics provides a framework to build visuals by combining geometries , scales , and aesthetics in a systematic way. In our example, the use of a bar geometry and the scale of the market share on the horizontal axis creates an immediately interpretable visual. This modular approach ensures that every element in the chart contributes to the clarity and overall goal of effective communication.

Eliminating Inappropriate Chart Types

In data visualization, some chart types are popular but not effective at conveying clear, actionable insights. The IBCS standards discourage the use of these chart types because they often distort information, waste space, or make comparisons difficult. Here’s how to eliminate these inappropriate chart types and replace them with more effective alternatives.

1. Replacing Pie and Donut Charts with Bar Charts

Before : Pie or donut charts are often used to represent proportions, such as sales by region. However, these charts make it difficult to compare slices accurately, especially when the differences are small.

After : Replace the pie or donut chart with a horizontal bar chart . Bar charts are much easier to read and allow for more precise comparisons between categories.

Replacing Gauges and Speedometers with Simple Line Charts

Before : Gauges or speedometers are often used in dashboards to show a single metric, like customer satisfaction or profit margins. However, they consume a lot of space and make it hard to track changes over time.

After : Replace gauges with a simple line chart that shows the trend of the metric over time. This not only conveys the current status but also provides context for how the metric is performing.

Replacing Radar Charts with Grouped Bar Charts

Before : Radar charts are used to compare multiple variables across categories, such as department performance metrics. However, the circular design is hard to interpret and makes comparisons less intuitive.

After : Replace radar charts with a grouped bar chart that presents the same data side by side. This allows for much clearer comparisons across categories and metrics.

Replacing Spaghetti Plots with Small Multiples or Line Charts

Before : Spaghetti plots with multiple overlapping lines make it difficult to follow individual trends, particularly when there are too many lines on the same chart.

After : Use small multiples (separate, simpler line charts for each category) or break down the plot into fewer, clearer line charts. This allows for easier interpretation of each individual trend.

Replacing Traffic Lights with Variance Analysis Charts

Before : Traffic lights (red, yellow, green) are often used to show status or performance indicators. While simple, they oversimplify complex data and lack context.

After : Replace traffic lights with a variance analysis chart that shows actual values against targets, enabling a more nuanced understanding of performance.

In each of these examples, we’ve replaced ineffective visualizations with IBCS-compliant alternatives that enhance clarity and make comparisons easier. By aligning with IBCS standards and leveraging concepts from the Grammar of Graphics , we ensure that data is expressed in a way that supports clear and informed decision-making.

Optimizing Data Representations

In data presentations, the way information is structured and represented can make all the difference. While it’s tempting to rely on lengthy textual descriptions or overly complex visuals, the IBCS standards encourage using quantitative representations wherever possible. Numbers, charts, and visualizations convey information more directly than text, and when done right, they can eliminate ambiguity and speed up understanding. This section will discuss how to optimize data representations according to IBCS principles and make use of quantitative visuals to avoid reliance on text-heavy slides.

Why Quantitative Representations Matter

Visualizing data quantitatively rather than explaining it in words provides immediate clarity and facilitates quicker decision-making. Consider a slide overloaded with paragraphs of text explaining key performance indicators (KPIs). It forces the audience to read and interpret, which slows down comprehension. In contrast, well-constructed charts, tables, or graphs can convey the same information in seconds.

IBCS emphasizes minimizing text and replacing it with visual elements that communicate the data clearly and effectively. This not only reduces cognitive load but also ensures the information is perceived accurately.

Example: Replacing Text-Heavy Slides with Charts

Before : Imagine a presentation slide with paragraphs of text explaining the company’s revenue growth over several years. The text describes the revenue trajectory and highlights which years saw increases or decreases.

After : Instead of text, replace this explanation with a simple line chart that clearly shows the revenue trend over time. A visual like this is much easier to understand at a glance, as it provides a direct view of the data without the need for lengthy descriptions.

This line chart immediately communicates the trend in revenue growth, making it clear which years saw increases and where the dips occurred — something that would have taken several paragraphs to explain in words.

The Role of the Grammar of Graphics

Leland Wilkinson’s Grammar of Graphics emphasizes the structured combination of elements such as scales , aesthetics , and geometries to create clean, informative visuals. In the example above, the line geometry and the use of scales on both the x-axis (years) and y-axis (revenue) allow for precise interpretation of the data. This approach transforms raw data into an easily digestible visual story that speaks for itself.

Avoiding Text-Only Slides

IBCS encourages replacing text-heavy slides with visuals wherever possible, but this doesn’t mean removing all text. The key is to balance text and visuals so that the text provides context while the visual delivers the core message.

For example, consider a slide that lists key performance indicators (KPIs) with lengthy descriptions of each one. Instead of using large blocks of text, create a table that lists the KPIs alongside the relevant figures, with minimal explanation.

Before : A slide with long descriptions of KPIs, such as:

• “The customer satisfaction score has increased by 10% from the previous quarter.”
• “Sales conversion rates are up by 15%, reaching the target of 75%.”

After : A simple chart that presents the KPIs clearly:

This visualized table allows the audience to immediately see the comparison between current performance and targets without the need for long explanations.

Best Practices for Optimizing Visuals

When optimizing your visuals, keep in mind these best practices, which are in line with both IBCS standards and the Grammar of Graphics :

• Simplicity : Strip away unnecessary details, labels, and decorative elements. Only include what is needed to communicate the data.
• Focus on Comparisons : Ensure that your visual enables clear comparisons, whether that’s between time periods, categories, or variables.
• Precision : Use scales and axes that accurately represent the data. Avoid distortions that can mislead the viewer.
• Balance of Text and Visuals : When text is necessary, keep it concise and complementary to the visual. Avoid long paragraphs and focus on what the audience needs to understand.

Enhancing Comparisons

One of the most powerful ways to make data meaningful is through comparisons. IBCS emphasizes the importance of showing comparisons clearly, whether between different scenarios, time periods, or variables. Comparisons help uncover trends, outliers, and relationships that would otherwise remain hidden. This section focuses on how to effectively incorporate comparisons into your reports, leveraging both IBCS standards and the Grammar of Graphics .

Why Comparisons are Critical

Without comparisons, data lacks context. For example, knowing that a company made $50 million in revenue last year is valuable, but it’s even more informative when compared to the previous year’s revenue, the industry average, or the company’s target.

Comparisons can be added in a variety of forms, such as:

• Time Comparisons : Comparing performance across different time periods (e.g., this quarter vs. last quarter).
• Scenario Comparisons : Showing different outcomes under various scenarios (e.g., best case, worst case, and expected case).
• Variance Analysis : Highlighting the difference between actual and target performance.
• Category Comparisons : Comparing different product lines, regions, or departments.

Example: Adding Variance Analysis for Target vs. Actual

Before : A report shows actual sales figures but doesn’t provide any context or comparison to targets.

After : By adding variance analysis  — comparing actual sales to target values — the report becomes much more meaningful. The audience can instantly see which regions met or missed their targets.

In this chart, we clearly see how each region performed against its target. The use of a variance analysis chart, where actual values are compared to targets using error bars, is a perfect way to communicate this comparison. The Grammar of Graphics enhances this process by using bars to represent actual performance and error bars to indicate target values. This direct comparison between actual and target performance makes it easy for the audience to spot areas of concern or success.

Enhancing Comparisons with Scenario Analysis Over Time

Before : A business report might present a single revenue forecast with no indication of uncertainty or alternative scenarios. This lacks context and doesn’t provide decision-makers with a full understanding of potential risks and opportunities.

After : By creating a scenario analysis line chart over time , we can show three scenarios — best case, expected case, and worst case — for a given metric (e.g., revenue) over several years. This allows stakeholders to see how different scenarios unfold and compare the potential outcomes in a more comprehensive way.

Interpreting the Scenario Analysis Over Time

In this scenario analysis, the best case scenario shows the most optimistic projection, where revenue grows consistently year after year. The expected case is a more conservative forecast with moderate growth, while the worst case anticipates a decline in revenue. The line chart makes it easy to compare these three scenarios over time, helping stakeholders understand the potential range of outcomes.

The Role of Grammar of Graphics in Scenario Analysis

This chart uses the line geometry to show trends over time for each scenario. The color aesthetic is used to differentiate the scenarios clearly, while the x-axis (years) and y-axis (revenue) allow the viewer to track changes over time. By using a consistent scale for all scenarios, we ensure that the audience can easily compare the growth or decline across the different scenarios.

Best Practices for Scenario Analysis Over Time

• Consistent Time Axis : Ensure that the time axis is the same for all scenarios, so that each scenario is directly comparable over the same period.
• Use Distinct Colors : Choose distinct and meaningful colors for each scenario (e.g., green for best case, red for worst case), so the viewer can easily differentiate between them.
• Highlight Key Points : Use markers (points on the line) to emphasize key moments in the forecast, such as sharp increases or decreases.

Small Multiples for Time Comparisons

Another effective technique for enhancing comparisons is the use of small multiples . Instead of cramming multiple lines into one chart (which can lead to spaghetti plots), small multiples create separate panels for each variable or time period, making comparisons across time much clearer.

Before : A single line chart shows revenue trends for multiple regions, with overlapping lines creating visual clutter.

After : Using small multiples, each region’s revenue trend is shown in a separate panel, making it easier to spot trends within each region while still allowing comparisons across regions.

Using facet grids creates a cleaner, more focused comparison of revenue trends for each region. This method keeps the charts easy to read, and the consistent scales across panels allow for straightforward comparisons between regions.

Best Practices for Effective Comparisons

When adding comparisons to your reports, here are some IBCS-aligned best practices to follow:

• Use Clear Scales : Ensure that all charts using comparisons have the same scale. Inconsistent scales can mislead the viewer and obscure important differences.
• Visualize Variances : Whenever possible, show the difference between actual and expected values, not just the raw numbers. Variance bars, error bars, and side-by-side comparisons are excellent for this.
• Avoid Overlapping Data : Use small multiples or grouped charts to break down complex datasets. This makes it easier for the audience to follow each variable or time series.
• Ensure Readability : Simplify the visual layout so that the key comparison is obvious at first glance. Avoid excessive labels or embellishments that distract from the main message.

Explaining Causes: Structure and Clarity

In data reporting, one of the most important tasks is to not only present data but to explain why certain outcomes occur. The IBCS standards recommend using tree structures to visually illustrate cause-and-effect relationships between key metrics. This helps decision-makers quickly understand the underlying factors that drive performance.

A tree structure is a hierarchical visual where a top-level metric is broken down into its contributing components. For example, profit can be broken down into its drivers, such as sales and costs . This method provides a clear visual flow, helping the audience trace back key figures to their source metrics.

In this section, we’ll explore how to use tree structures to explain causes, leveraging patchwork in R to create a multi-level visualization that breaks down a top metric into its sub-components over time.

Using Tree Structures to Explain Causes

Tree structures represent how a key metric is influenced by its underlying components, visually linking them in a cause-and-effect hierarchy. In a typical scenario, profit might be the top-level metric, which is influenced by sales and costs . These components can further be broken down into detailed metrics like units sold , price per unit , and fixed or variable costs .

This kind of breakdown not only shows what’s happening but also why it’s happening, making it easier for stakeholders to identify the drivers of success or areas of concern.

Example: Visualizing Profit Breakdown Using Patchwork

Let’s break down a company’s profit into its two key drivers: sales and costs . Each will be represented by its own chart, showing values across several quarters. Using the patchwork library, we’ll combine these charts into a tree structure, with profit at the top and sales and costs  below.

Before : In a typical report, profit, sales, and costs might be presented as individual, disconnected charts or numbers, without any clear visual indication of how they relate to each other.

After : We use a tree structure to link these metrics together, showing how profit is directly influenced by changes in sales and costs over time.

Here’s how you can create this structure in R:

Interpreting the Tree Structure

• Profit is placed at the top, showing how it evolves over four quarters (Q1–Q4).
• Sales and Costs are positioned below it, illustrating how these two components contribute to the overall profit.
• By linking these metrics visually, decision-makers can clearly see how changes in sales or costs directly affect  profit .

Expanding the Tree Structure

To provide even deeper insights, we can break down sales and costs into more specific components. For instance, sales can be split into units sold and price per unit , while costs can be divided into fixed and variable costs . This expanded tree structure helps the audience trace every dollar of profit back to its root causes.

Expanded Interpretation

• Sales is further broken down into units sold and price per unit , showing how both contribute to total sales across the quarters.
• Costs is split into fixed costs (which remain constant) and variable costs (which fluctuate), illustrating how each cost type impacts total costs.
• This expanded tree structure provides a deeper understanding of the components driving profit, allowing for a granular analysis of what’s affecting each metric.

Best Practices for Tree Structures in IBCS

• Start with the Key Metric : Place the top-level metric (e.g., profit) at the top of the structure and gradually break it down into its components.
• Show Time Trends : Using consistent time periods (e.g., quarters) across all metrics makes comparisons easier and reveals trends.
• Use Visual Links : Tree structures work best when they visually connect the metrics, clearly showing how each component contributes to the overall result.
• Keep the Layout Simple : Ensure the tree structure is easy to follow, with each chart clearly labeled and connected to its related metrics.

Beyond using tree structures to break down key metrics, other critical techniques for explaining causes in data reporting involve revealing correlations and clusters . These methods help uncover relationships between variables and group data points that share similar characteristics, allowing for deeper analysis of performance drivers.

Using Correlations to Reveal Relationships

In business reporting, it’s important to explain the relationships between different variables. For instance, you might want to know whether increasing advertising spend is correlated with an increase in sales. Correlation visualizations help demonstrate these connections, showing how one variable influences another.

Example: Visualizing Correlation Between Advertising Spend and Sales

Before : A report might present advertising spend and sales as separate figures or in separate charts, leaving it up to the reader to interpret any relationship.

After : A correlation scatter plot shows how changes in advertising spend are linked to sales, making the relationship between the two variables easy to interpret. A positive correlation, for example, could suggest that increasing advertising spend leads to higher sales.

Interpreting the Correlation Plot :

• Each point represents the relationship between advertising spend and sales for a particular period.
• The trend line shows the general direction of the relationship: a positive slope indicates that higher advertising spend correlates with higher sales.
• This visualization helps decision-makers assess whether investing more in advertising could drive additional sales, which might not be clear from viewing the figures in isolation.

Using Cluster Analysis to Group Data

Another powerful way to explain causes is through cluster analysis , which helps identify patterns or segments in your data. By grouping data points with similar characteristics, cluster analysis can reveal insights about different customer behaviors, product performance, or regional trends.

Example: Clustering Customer Purchase Behavior

Before : A report might list customer purchase behavior data by region, but it doesn’t reveal any patterns or similarities between different regions.

After : A cluster analysis plot groups customers based on similar purchase patterns, helping identify which regions or segments behave similarly, and how they differ from others. This provides actionable insights into regional strategies or product offerings.

Interpreting the Cluster Analysis :

• Each point represents a customer’s purchase amount in a given region.
• Color-coded clusters show which customers are grouped together based on similar purchasing behaviors. For example, regions like Asia might have higher purchase amounts than South America .
• Clustering allows for targeted actions, such as focusing marketing efforts on high-purchasing clusters or understanding what drives differences between segments.

Combining Tree Structures, Correlations, and Clusters

Tree structures, correlations, and clusters offer complementary ways to explain causes in data reporting:

• Tree Structures provide a hierarchical breakdown of metrics, showing how top-level results are derived from underlying factors.
• Correlations reveal relationships between different metrics, showing how changes in one variable may influence another.
• Clusters group similar data points together, highlighting patterns or segments that may not be obvious in the raw data.

Together, these techniques provide a rich, multi-faceted explanation of business performance, helping stakeholders understand both what is happening and why it’s happening.

Best Practices for Explaining Causes with Correlations and Clusters

• Highlight Relationships : When two variables are related, use correlation plots to make this relationship visually clear, especially when decision-makers need to see how one factor drives another.
• Cluster Similar Data : Use clustering when it’s important to group data points by similar behaviors or characteristics. This is especially useful for segmenting customers, regions, or product performance.
• Combine with Tree Structures : Use tree structures to provide the hierarchical context and breakdowns of key metrics, and enrich the analysis with correlation and cluster visuals to show deeper relationships or patterns.

Expressing with Purpose

Throughout this chapter, we have delved into the importance of using IBCS standards to enhance the way data is expressed in business reporting. As we’ve seen, the clarity and effectiveness of a report depend heavily on the proper selection of visualizations and their alignment with best practices. The IBCS framework’s emphasis on appropriate chart types , clear comparisons , and visual hierarchy transforms raw data into insightful, actionable information.

In the fast-paced environment of business intelligence, where decision-makers need to comprehend data quickly and accurately, the ability to express information clearly is critical. Reports that fail to meet these standards can lead to misinterpretation, confusion, or missed opportunities. By adhering to IBCS guidelines, you ensure that data reports are:

• Clear and focused : Free of unnecessary chart types that clutter or obscure insights.
• Consistent and standardized : Allowing stakeholders to easily understand, compare, and analyze the information without needing extra explanations.
• Actionable : Designed to emphasize key comparisons, causes, and insights that guide decisions.

These principles are not just about creating aesthetically pleasing charts but about communicating the right message with impact. Whether it’s ensuring your visuals provide clear comparisons, or using tree structures to explain causes, the IBCS standards provide a systematic approach to making data understandable and insightful.

Looking Ahead: The Importance of Integrating IBCS in Your Reporting

As we progress through this series on adapting IBCS standards into reporting, it’s important to recognize that the full power of IBCS lies in consistent application. By continuing to integrate these principles into every report, you’ll build a robust framework that delivers accurate and meaningful data to decision-makers.

But we’re not done yet! There are still two more chapters to go in this series, where we’ll dive deeper into other essential aspects of IBCS reporting. After completing the series, I’ll provide a comprehensive tutorial and framework that outlines how to choose the correct visualizations, validate them against IBCS standards, and adapt these guidelines to your specific reporting needs.

This final guide will serve as a step-by-step manual to ensure that every report you create is IBCS-compliant , leading to clearer, more effective communication in your organization.

Express to Impress: Leveraging IBCS Standards for Powerful Data Presentations was originally published in Numbers around us on Medium, where people are continuing the conversation by highlighting and responding to this story.

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