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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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How to Present Data in PowerPoint

PowerPoint has become an essential tool for anyone looking to present data in a clear and engaging way. But it’s not just about throwing numbers onto a slide and hoping for the best. Effective data presentation is a skill that takes practice and careful consideration to master. In this article, we’ll take you through everything you need to know about presenting data in PowerPoint, from understanding your audience to designing engaging slides and everything in between.

Table of Contents

Why Effective Data Presentation is Important in PowerPoint

Before we dive into the nuts and bolts of PowerPoint data presentations, let’s take a moment to understand why it’s so important. The main goal of any data presentation is to deliver information in a clear, concise way that engages your audience and helps them understand the significance of the data. This isn’t always easy – data can be complex, and if not presented effectively, it can lead to confusion, boredom, or even worse – disengagement.

By mastering the art of data presentation in PowerPoint, you can ensure that you’re delivering information in a way that your audience will respond to positively. This not only helps build credibility with your audience, but it can also be the difference between your message being heard and remembered, or ignored and forgotten.

Understanding Your Audience: Tailoring Your Data for Maximum Impact

One of the most important aspects of presenting data in PowerPoint is understanding your audience. Before you begin designing your presentation, take some time to think about who will be viewing it, and what their needs and expectations are.

For example, if you’re presenting to a group of executives, they’re likely to be interested in high-level, big-picture data that shows the overall direction of the company. Conversely, if you’re presenting to a team of analysts, they’ll be looking for more granular data that they can use to make specific decisions or recommendations.

By understanding your audience, you can tailor your data and presentation style to make the biggest impact. This might involve using different chart types, adjusting your tone of voice, or changing your visual style to better connect with your audience.

Choosing the Right PowerPoint Template for Your Data Presentation

The first step in designing an effective PowerPoint data presentation is choosing the right template. With so many options to choose from, it can be overwhelming to know where to start. Here are a few things to keep in mind when choosing a template:

• Consider your brand: Your presentation should reflect your brand’s visual identity, so look for templates that align with your brand standards.
• Simplicity is key: You want your data to be the star of the show, so avoid templates that are busy or overly complicated.
• Think about your audience: Consider the preferences and expectations of your audience when choosing a template. For example, if you’re presenting to a creative team, a more visually engaging template might be appropriate.

Ultimately, the goal of your template is to provide a clean, consistent backdrop for your data and visualizations to shine.

Top Tips for Designing Engaging PowerPoint Slides

Once you’ve chosen your template, it’s time to start designing your PowerPoint slides. Here are some tips to keep in mind:

• Use clear, legible fonts: Your data won’t be effective if it can’t be read, so choose fonts that are easy to read on-screen.
• Keep it simple: Avoid cluttering your slides with unnecessary bells and whistles. Your audience should be able to focus on your data without being distracted by overly complicated design elements.
• Use visuals to support your data: Visuals like charts, graphs, and images can help illustrate your data in a more engaging way than text alone.
• Be consistent: Use consistent formatting and design elements throughout your presentation to create a cohesive look and feel.

Remember, the goal of your PowerPoint slides is to support your data, not distract from it. Keep things simple and clear, and let your data do the talking.

Using Color and Contrast to Make Your Data Pop

Another important design consideration when presenting data in PowerPoint is color and contrast. These elements can help draw attention to key pieces of data and make your presentation more visually engaging.

Here are some tips for using color and contrast effectively:

• Use contrasting colors to highlight key data points: For example, you might use a bright color for a data point that demonstrates a significant change or achievement.
• Stick to a consistent color palette: Using too many colors can be distracting. Stick to a consistent color palette throughout your presentation to create a cohesive look and feel.
• Use color to create visual hierarchy: By using color to differentiate between headings, subheadings, and body text, you can create a visual hierarchy that guides your audience’s attention and helps them navigate the presentation more easily.

Remember, the goal of your use of color and contrast is to make your data more engaging and to help your audience understand its significance in a more visual way.

How to Choose the Right Chart Type for Your Data

When presenting data in PowerPoint, choosing the right chart type is essential. Different chart types are better suited for different types of data, so it’s important to choose one that accurately represents the story you’re trying to tell.

Here are some common chart types and when they might be appropriate:

• Line charts: Line charts are great for showing trends over time or for comparing multiple data sets.
• Pie charts: Pie charts are useful for showing how a whole entity is divided into different parts.
• Bar charts: Bar charts are ideal for comparing different entities or for showing changes in data over time.
• Scatter plots: Scatter plots are helpful for showing the relationship between two variables.

By choosing the right chart type, you can help your audience better understand the story your data is telling.

Creating Clear and Concise Labels and Titles

When presenting data in PowerPoint, it’s essential to use clear and concise labels and titles. This not only makes your data easier to read and understand, but it also helps your audience quickly identify the most important points in your presentation.

Here are some tips for creating effective labels and titles:

• Make it clear: Use labels and titles that accurately reflect the data you’re presenting.
• Keep it concise: Avoid long titles or labels that take up too much space and distract from your data.
• Be consistent: Use a consistent format for all of your labels and titles throughout the presentation to create a cohesive look and feel.

By creating clear and concise labels and titles, you can help guide your audience through your presentation more effectively.

Adding Animation and Transitions for a Professional Touch

Animation and transitions can be a great way to add a professional touch to your PowerPoint data presentation. However, it’s important to use them sparingly – too much animation can be distracting and take away from the data itself.

Here are some tips for using animation and transitions effectively:

• Keep it simple: Use subtle animations and transitions that enhance your data, rather than detracting from it.
• Use animation to highlight key data points: For example, you might use animation to draw attention to a particularly important data point or to show the progression of data over time.
• Be consistent: Use a consistent set of animations and transitions throughout your presentation for a cohesive look and feel.

By using animation and transitions effectively, you can make your data presentation more engaging and dynamic.

Presenting Your Data with Confidence: Tips for Public Speaking in PowerPoint

Finally, it’s important to remember that presenting data in PowerPoint is not just about the slides – it’s also about your delivery as a speaker. Here are some tips for presenting your data with confidence:

• Practice, practice, practice: The more familiar you are with your data and presentation, the more confident you’ll be when it’s time to present.
• Engage with your audience: Make eye contact, use positive body language, and speak clearly and confidently to keep your audience engaged.
• Use data to support your arguments: Use your data as evidence to support the points you’re making, rather than relying solely on your own opinions.

By following these tips, you can deliver a confident, engaging presentation that will leave a lasting impression on your audience.

Common Mistakes to Avoid When Presenting Data in PowerPoint

Now that we’ve covered some best practices for presenting data in PowerPoint, let’s take a look at some common mistakes to avoid:

• Cluttered slides: Too much information on a slide can be overwhelming and make it difficult for your audience to understand what’s important.
• Overly complicated charts: Choose charts that accurately represent your data, but avoid charts that are too complex or difficult to read.
• Too much text: Use visuals to support your data, and limit the amount of text on each slide to keep your audience engaged.

By avoiding these mistakes, you can ensure that your data presentation is engaging, clear, and effective.

Best Practices for Saving and Sharing Your PowerPoint Presentation

Once you’ve put the finishing touches on your PowerPoint data presentation, it’s important to make sure it’s saved and shared correctly. Here are some best practices to keep in mind:

• Save often: Make sure you save your presentation regularly to avoid losing any work.
• Compress images and videos: Large images and videos can make your presentation file size very large. To avoid this, compress any images or videos you include in your presentation.
• Save in different formats: Depending on who you’ll be sharing your presentation with, you may want to save it in different formats, such as PDF or JPEG.

By following these best practices, you can ensure that your presentation is saved and shared safely and effectively.

Creative Ways to Present Complex Data in PowerPoint

Presenting complex data in PowerPoint can be a challenge, but there are creative ways to make it more engaging. Here are some ideas:

• Use infographics: Infographics can be a great way to make complex data more visually engaging and easy to understand.
• Use animations and transitions: Animations and transitions can help break down complex data into more digestible chunks.
• Use storytelling: Telling a story with your data can help it feel more relatable and engaging.

By using creative techniques like these, you can make even the most complex data more engaging and approachable.

How to Use Infographics and Visuals to Enhance Your Data Presentation in PowerPoint

Finally, let’s take a closer look at the ways you can use infographics and visuals to enhance your PowerPoint data presentation. Here are some tips:

• Use icons to illustrate points: Icons can help illustrate complex points in a simple, engaging way.
• Use diagrams and flowcharts: Diagrams and flowcharts can help illustrate processes or systems more clearly than text alone.
• Use images and videos: Images and videos can help bring your data to life and make it more engaging and relatable.

By using visuals strategically, you can create a PowerPoint data presentation that is both informative and engaging.

Resources for Further Learning on Presenting Data in PowerPoint

If you’re interested in learning more about presenting data in PowerPoint, there are many resources available to help you improve your skills. Here are a few to get you started:

• Microsoft’s PowerPoint training center: Offers courses and tutorials on presenting data in PowerPoint.
• Lynda.com: Offers a wide variety of courses on PowerPoint data presentation.
• Data Presentation Tips: A blog devoted to tips and techniques for presenting data in a way that is engaging and effective.

By taking advantage of these resources and continuing to refine your skills, you can become a master of presenting data in PowerPoint.

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10 Tips for Presenting Data

Big data. Analytics. Data science. Businesses are clamoring to use data to get a competitive edge, but all the data in the world won’t help if your stakeholders can’t understand, or if their eyes glaze over as you present your incredibly insightful analysis . This post outlines my top ten tips for presenting data.

It’s worth noting that these tips are tool agnostic—whether you use Data Studio, Domo, Tableau or another data viz tool, the principles are the same. However, don’t assume your vendors are in lock-step with data visualization best practices! Vendor defaults frequently violate key principles of data visualization, so it’s up to the analyst to put these principles in practice.

Here are my 10 tips for presenting data:

• Recognize that presentation matters
• Don’t scare people with numbers
• Maximize the data pixel ratio
• Save 3D for the movies
• Friends don’t let friends use pie charts
• Choose the appropriate chart
• Don’t mix chart types for no reason
• Don’t use axes to mislead
• Never rely solely on color
• Use color with intention

1) Recognize That Presentation Matters

The first step to presenting data is to understand that how you present data matters . It’s common for analysts to feel they’re not being heard by stakeholders, or that their analysis or recommendations never generate action. The problem is, if you’re not communicating data clearly for business users, it’s really easy for them to tune out.

Analysts may ask, “But I’m so busy with the actual work of putting together these reports. Why should I take the time to ‘make it pretty’?”

Because it’s not about “making things pretty.” It’s about making your data understandable.

My very first boss in Analytics told me, “As an analyst, you are an information architect.” It’s so true. Our job is to take a mass of information and architect it in such a way that people can easily comprehend it.

Take these two visuals. The infographic style shows Top 10 Salaries at Google. The first one is certainly “prettier.” However, the visual is pretty meaningless, and you have to actually read the information to understand any of it. (That defeats the purpose of a data viz!)

Pretty, but not helpful

On the flip side, the simpler (but far less pretty) visualization makes it very easy to see:

• Which job category pays the most
• Which pays the least
• Which has the greatest range of salaries
• Which roles have similar ranges

It’s not about pretty. When it comes to presenting data clearly, “informative” is more important than “beautiful.”

Just as we optimize our digital experiences, our analyses must be optimized to how people perceive and process information. You can think of this as a three-step process:

• Information passes through the Visual Sensory Register . This is pre-attentive processing—it’s what we process before we’re even aware we’re doing so. Certain things will stand out to us, objects may get unconsciously grouped together.
• From there, information passes to Short Term Memory. This is a limited capacity system, and information not considered “useful” will be discarded. We will only retain 3-9 “chunks” of visual information. However, a “chunk” can be defined differently based on how information is grouped. For example, we might be able to remember 3-9 letters. But, we could also remember 3-9 words, or 3-9 song lyrics! Your goal, therefore, is to present information in such a way that people can easily “chunk” information, to allow greater retention through short-term memory. (For example, a table of data ensures the numbers themselves can’t possibly all be retained, but a chart that shows our conversion rate trending down may be retained as one chunk of information—“trending down.”)
• From short-term memory, information is passed to Long-Term Memory. The goal here is to retain meaningful information—but not the precise details.

2) Don’t Scare People with Numbers

Analysts like numbers. Not everybody does! Many of your stakeholders may feel overwhelmed by numbers, data, charts. But when presenting data, there are little things you can do to make numbers immediately more “friendly.”

Simple formatting

Don’t make people count zeros in numbers! (e.g. 1000000 vs. 100,000,000).

Skip unnecessary decimals

How many decimals are “necessary” depends on the range of your values. If your values range from 2 to 90 percent, you don’t need two decimals places.

But on the flip side, if you have numbers that are really close (for example, all values are within a few percent of each other) it’s important to include decimal places.

Too often, this comes from confusing “precision” with “accuracy.” Just because you are more precise (in including more decimal places) doesn’t make your data more accurate. It just gives the illusion of it.

Right align numbers

Always right-align columns of numbers. This is the default in many solutions, but not always. What it allows for is your data to form a “quasi bar chart” where people can easily scan for the biggest number, by the number of characters. This can be harder to do if you center-align.

3) Maximize the Data-Pixel Ratio

The Data-Pixel Ratio originally stems from Edward Tufte’s “Data-Ink Ratio”, later renamed the “Data-Pixel Ratio” by Stephen Few. The more complicated explanation (with an equation, GAH!) is:

A simpler way of thinking of it: Your pixels (or ink) should be used for data display, and not for fluff or decoration. (I like to explain that I’m just really stingy with printer ink—so, I don’t want to print a ton of wasted decorations.)

Here are some quick transformations to maximize the data-pixel ratio:

Avoid repeating information

For example, if you include the word “Region” in the column header, there’s no need to repeat the word in each cell within the column. You don’t even need to repeat the dollar sign. Once we know the column is in dollars, we know all the values are too.

Avoid repeating information when presenting data

For bar and column charts:

• Remove borders (that Excel loves to put in by default, and Google Sheets still doesn’t let you remove them, grumble grumble.)
• Display information horizontally. Choosing a bar over a column chart can make the axis easier to read.
• Condense axes, to show values “in Millions” or “in K”, rather than unnecessarily repeating zeros (“,000”)

For line charts:

• Remove unnecessary legends. If you only have one series in a line chart, the title will explain what the chart is—a legend is duplicated information.
• Grey (or even remove) grid lines. While sometimes grid lines can be useful to help users track across to see the value on the y-axis, the lines don’t need to be heavy to guide the eyes (and certainly not as visually important as the data).

4) Save 3D for the Movies

These two charts have the same information. In the top left one, you can see at a glance that the bar is slightly above $150,000. In the bottom one, you can “kind of sort of tell” that it’s at $150,000, but you have to work much harder to figure that out. With a 3D chart you’re adding an extra cognitive step, where someone has to think about what they’re looking at.

And don't even get me started on this one:

However, I’ll concede: there is an exception to every rule. When is 3D okay? When it does a better job telling the story , and isn’t just there to make it “snazzy.” For example, take this recent chart from the 2016 election: 3D adds a critical element of information, that a 2D version would miss.

5) Friends Don’t Let Friends Use Pie Charts

It’s easy to hate on pie charts (and yet, every vendor is excited to announce that they have ZOMG EXPLODING DONUT CHARTS! just added in their recent release).

However, there are some justified reasons for the backlash against the use (and especially, the overuse) of pie charts when presenting data:

• We aren’t as good at judging the relative differences in area or circles, versus lines . For example, if we look at a line, we’re more easily able to say “that line is about a third bigger.”We are not adept at doing this same thing with area or circles, so often a bar or column chart is simply easier for us to process.
• They’re used incorrectly . Pie charts are intended to show “parts of a whole”, so a pie chart that adds up to more than 100% is a misuse of the visualization.
• They have too many pieces . Perhaps they do add up to 100%, but there’s little a pie chart like this will do to help you understand the data.

With that understood, if you feel you must use pie charts, the following stipulations apply:

• The pie chart shouldn’t represent more than three items.
• The data has to represent parts of a whole (aka, the pieces must add to 100%).
• You can only use one. As soon as you need to compare data (for example, three series across multiple years) then pie charts are a no-go. Instead, go for a stacked bar chart.

Like 3D, pie charts are acceptable when they are the best possible way for presenting data and getting your message across. This is an example of where, hands-down, a pie chart is the right visualization:

6) Choose the Appropriate Chart for Presenting Data

A chart should be carefully chosen, to convey the message you want someone to take from your data presentation. For example, are you trying to show that the United States and India’s average order value are similar? Or that India’s revenue is trending up more quickly? Or that Asia is twice the rest of the world?

For a more comprehensive guide, check out Extreme Presentation’s Chart Chooser. But in the meantime, here is a quick version for some commonly used charts:

Line charts

Use line charts to demonstrate trends. If there are important things that happened, you can also highlight specific point

Bar or column charts

Bar or column charts should be used to emphasize the differences between things.

If you don’t have much space, you might consider using sparklines for presenting data trends. Sparklines are a small chart contained within a single cell of a table. (You can also choose to use bar charts within your data table.)

Here are some resources on how to build sparklines into the different data viz platforms:

Google Sheets

7) Don’t Mix Chart Types for No Reason

I repeat. Don’t mix chart types for no reason . Presenting data sets together should tell a story or reveal insights together, that isn’t possible if left apart. Unfortunately, far too many charts involving cramming multiple data series on them is purely to conserve the space of adding another chart. The problem is, as soon as you put those two series of data together, your end users are going to assume there’s a connection between them (and waste valuable brain power trying to figure out what it is).

Below are good and bad examples of mixing chart types when presenting data. On the first, we have a column and line chart together, because we’re trying to demonstrate that the two metrics trend similarly. Together they are telling a story, that they wouldn’t tell on two separate charts.

The second, however, is an example of “just trying to fit two series onto a chart.”

For the second chart, a better option for presenting the data might be to have two side-by-side bar or column charts.

8) Don’t Use Axes to Mislead

“If you torture the data long enough, it will confess to anything” – Ronald Coase

One easy way to mislead readers is to change the axes of your data. Doing so quickly magnifies what might be small differences, and can distort the story your data is telling you. For example, starting the axis at 155,000 makes the differences between the highs and lows look more dramatic.

In the next example, the line chart doesn’t actually correspond to the axis! (Did you know 8.6 is more than 8.8?!)

The most truthful option is to always start your axes at zero. But sometimes, we need to show differences in metrics that don’t shift much over time. (For example, our conversion rate might range between 1.0% and 1.3% from month to month.) In that case, my recommendation would be to show the more truthful axis starting at zero, but provide a second view of the chart (a “zoomed in view”, so to speak) that shows a smaller range on the axis, so you can see the month-to-month change.

9) Never Rely Solely on Color When Presenting Data

Color is commonly used as a way to differentiate “good” vs. “bad” results, or “above” or “below” target. The problem is, about ten percent of the population is colorblind! And it’s not just red/green colorblind (though that’s the most common). There are many other kinds of colorblindness. As a result, ten percent of your stakeholders may actually not be comprehending your color scheme. (Not to mention, all black and white printers are “colorblind.”)

That doesn’t mean you can’t use any red or green (it can be an easily understood color scheme) when presenting data. But you do have to check that your data visualization is understandable by those with colorblindness, or if someone prints your document in black and white.

Additionally, there are also differences in how colors are perceived in different cultures. (For example, red means “death” in some cultures.) If you are distributing your data presentation globally, this is an additional factor to be conscious of.

10) Use Color with Intention

In the below chart, the colors are completely meaningless. (Or, as I like to call it, “rainbow barf.”)

Being careful with color also means using it consistently. If you are using multiple charts with the same values, you have to keep the colors consistent. Consider the tax on someone’s interpretation of your visualization if they constantly have to think “Okay, Facebook is blue on this chart, but it’s green on this other one.” Not only are you making them think really hard to do those comparisons, but more likely, they’re going to draw an incorrect conclusion.

So be thoughtful with how you use color! A good option can be to use brand colors. These are typically well-understood uses of color (for example, Facebook is blue, YouTube is red.) This may help readers understand the chart more intuitively.

(Data Studio only recently added a feature where you can keep the colors of data consistent across charts!)

Another user-friendly method of using color intentionally is to match your series color to your axis (where you have a dual-axis chart). This makes it very easy for a user to understand which series relates to which axis, without much thought.

Bonus Tip 11. Dashboards Should Follow The Above Data Visualization Rules

So, what about dashboards? Dashboards should follow all the same basic rules of presenting data, plus one important rule:

“A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.” -Stephen Few (Emphasis added.)

Key phrase: “on a single screen.” If you are expecting someone to look at your dashboard, and make connections between different data points, you are relying on their short-term memory. (Which, as discussed before, is a limited-capacity system.) So, dashboards must follow all the same data viz rules, but additionally, to be called a “dashboard”, it must be one page/screen/view. (So, that 8 page report is not a “dashboard”! You can have longer “reports”, but to truly be considered a “dashboard”, they must fit into one view.)

I hope these tips for presenting data have been useful! If you’re interested in learning more, these are some books I’d recommend checking out:

The Wall Street Journal Guide to Information Graphics

Information Dashboard Design

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17 Data Visualization Techniques All Professionals Should Know

• 17 Sep 2019

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

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

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

Access your free e-book today.

What Is Data Visualization?

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

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

Data Visualization Techniques

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

Here are some important data visualization techniques to know:

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

1. Pie Chart

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

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

2. Bar Chart

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

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

3. Histogram

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

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

4. Gantt Chart

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

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

5. Heat Map

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

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

6. A Box and Whisker Plot

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

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

7. Waterfall Chart

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

8. Area Chart

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

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

9. Scatter Plot

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

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

10. Pictogram Chart

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

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

11. Timeline

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

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

12. Highlight Table

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

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

13. Bullet Graph

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

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

14. Choropleth Maps

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

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

15. Word Cloud

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

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

16. Network Diagram

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

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

17. Correlation Matrix

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

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

Other Data Visualization Options

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

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

Tips For Creating Effective Visualizations

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

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

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

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

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

Related : Bad Data Visualization: 5 Examples of Misleading Data

Visuals to Interpret and Share Information

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

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

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

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

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Home Blog Business How to Design a Dashboard Presentation: A Step-by-Step Guide

How to Design a Dashboard Presentation: A Step-by-Step Guide

What do all businesses have in common? They all create data. Nevertheless, they differ in how they use the data to make informed business decisions.

Are you ready to make better decisions for your business? Do you want to use the data your business piles up effectively? It’s time to start using dashboard presentations.

This quick guide will take you on a journey to create a data dashboard presentation highlighting metrics and KPIs needed to make essential decisions about any business scenario.

Table of Contents

• What is a Dashboard Presentation?
• Why do you need a Dashboard for your business?

Anatomy of an Effective Dashboard Presentation

• Metrics and KPIs to include in your dashboard

Step-by-Step Guide to creating a dashboard presentation

How to present a dashboard in powerpoint, recommended state-of-the-art tools to create a dashboard, a quick look at excel dashboards, closing thoughts, what is a dashboard presentation .

A data dashboard is a versatile and practical tool for making important decisions. It’s the solution to time-consuming data research that expands across multiple locations. 

In business, you have various tools to keep you informed on performance and growth. Your sales platforms, marketing applications, and customer service software collect data. Looking through data on different locations takes up time, and that’s where custom dashboards come in. 

Dashboards bring together data in one place to answer specific questions and tell stories about your business. Data dashboards can be created in several ways, depending on their level of interactivity and real-time data updates. 

To be truly effective, a dashboard needs a hierarchical strategy. One or more main dashboards answer the big questions, while others answer specific questions per team, time frame, or campaign. 

Live dashboards update at regular intervals, pulling data from many sources simultaneously, offering a real-time overview of the big picture. 

Dashboard presentations display data for a specific point in time, a snapshot to share with stakeholders and managers. This is the type of presentation you can create today using PowerPoint and editable presentation templates by SlideModel.

Why do you need a Dashboard for your business? 

Every business generates data about customers, employees, production lines, communication platforms, etc. All the collected data is valuable information for making informed business decisions. That said, only some in a company know how to manually dig into data spreadsheets to find trends, sudden changes, and other business metrics. A dashboard fixes that.

Not all business data lives in the same place, most of which isn’t visual. In a dashboard, you bring together data from different sources, choose the metrics you need for that dashboard and make it all look coherent and easy to understand.

There are more benefits than setbacks when using dashboards, especially when they’re created efficiently and follow a straightforward data story.

Here’s a list of the most significant benefits of using dashboard presentations in your meetings and strategy sessions:

• Data dashboard presentations help you and your team make better, more informed decisions.
• They provide a coherent and detailed overview of your business’ KPIs and metrics for a specific strategy, campaign, or hypothesis.
• Dashboard presentations facilitate analysis and understanding of how different metrics and dimensions have different outcomes.
• They improve accountability in a team as everyone can see what needs improvement and what is reaching set benchmarks.
• Using data dashboards as a team makes sense. To work together towards a common goal, everyone must know what’s at stake.

How to Design an Efficient Dashboard Presentation  

Creating a dashboard presentation for the first time can feel a bit daunting. This guide takes you step-by-step through the process from strategy to completion.

Click on the sections below if you’d like to skip ahead.

The layout for a dashboard presentation depends on the aspect ratio you need to work with. The aspect ratio will depend on how your audience views and uses the dashboard.

For a desktop or computer view, a horizontal 16:9 ratio is suitable. A scrolling dashboard is better on mobile devices—just remember to highlight the hierarchy in the data. The optimal dashboard presentation is responsive to different screen sizes. 

Before we get into the KPIs and the step-by-step guide, let’s visualize the anatomy of a dashboard presentation. Here are some actionable guidelines to help you.

Giving the dashboard a title

The dashboard title doesn’t need to be too large; remember that you need space in the canvas to display the data. If necessary, include a subtitle with essential information. Don’t add it if it’s not needed to understand the dashboard. 

The location of the title is preferably at the top left or top center. To the left, leaves space to the right for a couple of data points; the centered option will have white space on the sides.

Grouping Big numbers and data visualizations

The most efficient way to organize the information on your dashboard is to group the data points into relevant categories. Creating these groups has two purposes; it helps with the overall layout and hierarchy of the dashboard, and it supports the cognitive analysis done by the viewer.

As you create groups of data points, place similar visualizations inside groups to maintain a visual balance. For example, at the very top, it’s common to have a horizontal section with a group of big numbers. 

Big numbers are data points that highlight an exact number or value at a specific time. Some big numbers include; overall revenue, profit, number of followers, number of support calls completed, etc. Likewise, big numbers can be the percentage reached towards a goal or the progress of a specific action. 

Group data visualizations or similar charts into more sections to place below the big numbers. This technique uses human reading patterns to create a visual hierarchy for the dashboard, making it easier to understand at a glance.

Adding visual metaphors

There’s no need to use just numbers and charts inside a dashboard. Take advantage of visual metaphors to help highlight the data in their sections. This is a common technique for creating infographics . 

A dashboard’s most used visual metaphor is a data point’s negative or positive impact. For this purpose, you can add arrows , color labels, up and down thumbs, happy and sad faces, or a visual thermometer highlighting the current amount of money collected in a fundraising campaign. Which style, depends on the dashboard’s business tone. For a financial dashboard, color labels are enough, but emojis are just as adequate for a young startup’s sales rep dashboard.

Crafting legends and captions 

Data points and data point groups will be more precise with a caption or label accompanying them. Place short labels in the exact location in each group, and place legends in similar areas to each data point. This visual consistency makes the data easier to review.

We can’t stress enough how important it is to choose the right font for your dashboard. It needs to be easy to read at small sizes and consistent throughout the layout. Forget about using two fonts or more. Use one and highlight selected text with bold or italic styling.

Supporting analysis with filters

Adding filters to a dashboard is a choice you’ll have to make with your team. First, why filters? A filter is a selection tool to choose between views in the dashboard. Standard filters include time frame, location, people, etc.

Regarding dashboard presentations, filters don’t work the same way as they do on Excel dashboards. In an Excel dashboard, filters are integrated into the data points. When used, the data in the dashboard changes dynamically. You’ll have to create separate views on different slides in a dashboard presentation.

Metrics and KPIs to include in your dashboard 

The content in a dashboard is metrics, dimensions, and KPIs , but how do you know which ones to include? There’s no one answer to this question; every dashboard is different. But thankfully, there are some general foundations you can follow.

First, you need to know the strategy to determine what metrics and KPIs you’ll need. Think of this as a playbook for every dashboard you create.

• Have a clear grasp of the dashboard’s purpose and goal. Know the answers to the questions in Step 1 of the step-by-step guide.
• Formulate one or more hypotheses or questions as a base for the analysis.
• Study the data you have on hand and select the metrics and KPIs that highlight what you need to know about your hypothesis or question.
• Outline the data sets in a hierarchy of importance and relevance.

This playbook will guide your decision on what metrics and KPIs to use, regardless of your profession and industry. Here are some example KPIs and templates to help give you a better idea

A social media dashboard that asks questions about engagement and brand awareness would use weekly KPIs like:

• Follower growth
• Engagement to follower count ratio
• Measurement of clicks on links
• Hashtag tracking
• Comment and DM tracking
• Best all-around post

The marketing dashboard template below highlights the following:

• Conversions
• Browser preference
• Performance

Download it to start using it with PowerPoint to create your following marketing dashboard. If you’re looking for marketing campaign dashboards, browse our template gallery.

A retail company asks for a dashboard highlighting how online and in-store sales are leveling up after the pandemic. These would be good KPIs to include:

• Overall sales in the stores and online
• Product category sales that differ in online and in-store purchases
• Trends over time
• Return rates for online and in-store sales
• Demographic data about the customer

Below is one of our sales dashboard templates . There’s a summary dashboard on the first slide and consecutive slides with detailed data. These are some of the metrics it highlights:

• Weekly sales
• Product share
• Predicted vs. actual sales
• Sales over time

Customer Service/Support

A dashboard highlighting the successes and fails of the customer support team would use metrics like these :

• Customer satisfaction score
• Customer effort score
• Total tickets + tickets per customer
• Volume by channel (chat, phone, email, etc.)
• First response time
• Average handle time
• Cost per resolution
• Net promoter score

Look at this customer service KPI dashboard template that uses most KPIs mentioned above. Note that first response time and average handle time are all metrics you can get from your business phone system .

Project Management

These are the common metrics in a project dashboard , you can add or take away depending on your particular dashboard purpose:

• Planned Value 
• Actual Cost
• Earned Value 
• Cost Variance (Planned Budget vs. Actual Budget)
• Cost Performance Index 
• Planned hours of work vs. actual situation

Alternatively, you can use a roadmap dashboard with a Gantt chart and other important KPIs highlighting progress.

Financial Operations 

Financial dashboards tend to get very busy visually. They usually also have more line charts than others. Here are a few of the most common KPIs for a financial dashboard presentation.

• Operating Cash Flow (OCF)
• Current Ratio
• Net Profit Margin
• Sales Growth
• Vendor Expenses

This financial dashboard template , for example, has 12 data points in one space. It’s a great example of how design and dashboard storytelling techniques help create a beautiful dashboard.

Now it’s time to get into the nitty-gritty, the how-to for creating a dashboard presentation

These steps cover what you need to know to create an efficient dashboard presentation with PowerPoint and SlideModel. 

Step 1: Define the purpose of your dashboard presentation

Dashboards are born from a business need, a way to quickly analyze data and make informed decisions. That’s why it’s essential to know your dashboard’s purpose before you do anything. 

It could be as broad as a CEO saying they have 30 seconds to see a dashboard once a week. Or a high-level manager wants to see an overview of the activity in their department at the Monday morning meetings. And yet another could be the social media manager’s need to show progress over time regarding a specific campaign.

Here are the questions you need to answer before continuing:

• Who will be the end users?
• What are their key business goals and objectives?
• What are the most important questions they need answers to?
• How frequently will the dashboard be reviewed?

With the answers to this checklist, you’re ready to go on to the next step.

Step 2: Choose the right metrics for your purpose

Above, we show you how to choose the KPIs for your dashboard. You might already have some data inside several business platforms’ analytics sections. Others you might have to source in other ways. 

As you collect the data, analyze the level of detail you’ll need to visualize. It will help later when transforming the data from its original form to a data visualization on the dashboard.

For each data point, take note of what it’s highlighting. What exact question is it answering? These will turn into legends and captions when you put them all together.

Step 3: Present the data effectively

With the metrics and KPIs collected, it’s time to present them on the dashboard. It’s essential to write down a hierarchical outline of the data points. Start with the most critical data according to the question the dashboard aims to answer. 

For each data point, select a style of visualization; big numbers, percentages, bar charts, simplified line graphs, and arrays. Write it all down on the outline. Use big numbers at the top of the dashboard to highlight the most influential data. Don’t use too many data visualization of the same style together; the repetition affects the viewer’s attention. 

Before adding the data to PowerPoint, prepare your charts to export them easily. Ensure the data is cleaned and revised, and there’s no extra irrelevant information. 

Step 4: Eliminate visual clutter and noise

Once you have all the KPIs on the dashboard, check for unnecessary visual material. Are you using the same font for all data points? Is the color unified across the design? How about text size and alignment?

Give each data point a margin of space around it. Keep the distance between data points and groups similar in size. Keep lines as straight as possible without much overlap between data points. Resize and shape each data point so it aligns neatly on the dashboard.

Check the text in the chart and graph legends. Make sure to keep all legends and labels similar in size and easy to read. Don’t use colored text or styled text unless it serves a purpose.

Step 5: Use the layout to focus attention

To structure the layout of your dashboard, take note of the human act of reading. People read from left to right, starting in the top left corner of the page or screen. Their gaze continues in a back-and-forth motion that resembles the letters Z and F. Knowing where your viewer will most likely look first, place your most important, high-level data in their line of sight.

Remember to combine similar data points to create visual separations in the layout. Help the viewer follow the flow of information with subtle design elements like color, size, and position. Apply Gestalt principles like proximity and similarity to group elements together.

Step 6: Tell a clear story

Why is it important to tell a story with data on your dashboard? If you were to phrase your dashboard’s purpose as a question or hypothesis, the data would be the answer. Use descriptive titles and labels to help the viewer understand the data in order of importance.

As the viewer scans the data on the dashboard, comprehension must start at the top with the top-level data points. These answer the most immediate question of the dashboard’s purpose, like the opener of a story or essay. The story continues with the rest of the data points, which will complete the analysis. 

When you tell a clear story with the help of a hierarchic layout, descriptive titles, and labels, the data story flows naturally. To achieve a compelling data story for your dashboard, ask for feedback from your team and edit the layout until it makes sense.

Presenting a dashboard on PowerPoint is simple. Depending on what type of dashboard you need, there’s a way to do it. 

You only need the collected data and one of our dashboard templates to create and present a static dashboard presentation with PowerPoint. The step-by-step guide above will help. 

For dynamic and interactive dashboards in PowerPoint, you’ll have to connect to your live data on Excel using a tool like Presentation Point . Alternatively, you can embed Power BI and Excel dashboards into your PowerPoint slides.

Let’s take a quick look at the recommended data dashboard tools. For a static dashboard presentation, our preferred tool is PowerPoint. But for highly interactive and dynamic dashboards with live data updates, you’ll need something else.

Looker Studio (previously Google Data Studio)

Looker Studio is the new name of Google Data Studio. With this tool, you can create dashboards and reports to showcase and highlight KPIs regardless of your business type. Adding a Looker Studio dashboard to a PowerPoint presentation isn’t ideal. There’s no intuitive process, and it isn’t recommended. Looker Studio is better suited for teams that work with the G-Suite.

Microsoft Excel

Excel dashboards are a classic reporting staple in the world of business. You can create elaborate dashboards with dynamic and interactive features using data sources, reference tables, and pivot tables. Stay tuned if you have ever wondered how to create an Excel dashboard that updates automatically.

Power BI (Business Intelligence) is a Microsoft tool for visualizing data insights that help make better business decisions. It is the tool of choice for big companies with large amounts of data to be analyzed. Connecting and embedding Power BI dashboards to PowerPoint is simple since they’re both from Microsoft.

Tableau is similar to Power BI in that they are both data visualization platforms that improve business intelligence. Tableau dashboards are a great alternative to Power BI and can also be embedded into a PowerPoint presentation. 

SlideModel + PowerPoint

Finally, the combo between SlideModel and PowerPoint comes into the picture. This duo is your best friend when creating static dashboard presentations.

Use SlideModel dashboard presentation templates to create a static dashboard that gives an insightful overview of some aspects of your business. Share the dashboard with your team and make better decisions together.

To create a live data dashboard presentation with SlideModel and PowerPoint, try Presentation Point, a tool to help bring live data into your presentations. Alternatively, you can try our AI PowerPoint generator to create a custom companion slide deck for your presentation topic.

As we mentioned above, Excel is an epic tool for business dashboards. It’s more accessible than Power BI and easier to use than Tableau (especially if you’re already an Excel pro). To create an Excel dashboard, you need to set up at least four sheets that work together to highlight the KPIs. They are:

• Data source sheets  
• Reference tables sheets   
• Pivot Tables sheets 
• The Dashboard sheet 

The best part about creating Excel dashboards is the possibility of building dynamic dashboards with data that updates automatically. Our favorite part? You can then embed it in PowerPoint and use SlideModel templates to make it all visually cohesive.

If you didn’t already know, dashboards are unique. They’ve been fantastic business tools for years. It’s no surprise they’ve jumped to other information design fields. For example, dashboard-style CVs! 

Creating a static data dashboard presentation (as a CV or for your business) is much easier when you know your needed tools. Some are easier than others, while others are too much for your needs.

Since you’re creating a data dashboard presentation with static data, you only need a PowerPoint and SlideModel. Browse our library to find digital marketing dashboard templates, HR dashboard templates, and lots more. 

Here’s to your next presentation dashboard. May it be the best you’ve ever made.

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Dashboard, Data Visualization, Visualization Ideas Filed under Business

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10 Methods of Data Presentation with 5 Great Tips to Practice, Best in 2024

Leah Nguyen • 05 April, 2024 • 17 min read

There are different ways of presenting data, so which one is suited you the most? You can end deathly boring and ineffective data presentation right now with our 10 methods of data presentation . Check out the examples from each technique!

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 in the types of presentation that have the flawless clarity of a diamond? So, let’s check out best way to present data. 💎

Table of Contents

• What are Methods of Data Presentations?
• #1 – Tabular

#3 – Pie chart

#4 – bar chart, #5 – histogram, #6 – line graph, #7 – pictogram graph, #8 – radar chart, #9 – heat map, #10 – scatter plot.

• 5 Mistakes to Avoid
• Best Method of Data Presentation

Frequently Asked Questions

More tips with ahaslides.

• Marketing Presentation
• Survey Result Presentation
• Types of Presentation

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What are Methods of Data Presentation?

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 for cutting 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.

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.

Bonus example: A literal ‘pie’ 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 presentation of data. 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.

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.

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).

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.

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 .

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

Most U.S 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.

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 quiz 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 set your session with open-ended questions , to avoid dead-communication!

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👇

What is 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 presentation?

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

Why should use charts for presentation?

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

What are the 4 graphical methods of presenting data?

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

Leah Nguyen

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

Tips to Engage with Polls & Trivia

More from AhaSlides

15 Cool Ways to Show Data

The different methods of showing data in a pictorial form, graphical, and visual context enable decision-makers to grasp difficult concepts or define trends.

No matter if you want to visualize a data flow, data comparison or you need to show data over time as a trend, there are many variants of visual communication.

Here we collected 15 examples of creative and cool ways to show data in statistics, business, marketing, finance and etc.

1. Venn Diagram

If you need to make a comparison between 2 relatively simple data sets, Venn diagram can be your creative and cool solution. Venn diagram is an illustration that uses circles to shows logical relationships between two or more sets (grouping items).

Typically, Venn diagrams show how given items are similar and different. Venn diagram with 2 or 3 circles is the most common type. But there are also many diagrams with a larger number of circles (5,6,7,8,10…).

2. Bubble Chart 

Bubble Chart is one of the most attractive types of graphs  and charts available in statistics and business.

Bubble charts are super useful charts for making a comparison of the relationships between data in 3 numeric data dimensions: the Y-axis data, the X-axis data, and data depicting the bubble size.

If you want to display three or four dimensions of data or you want to compare and display the relationships between categorized circles, bubble charts can be your answer.

3. Decision Trees

As graphical representations of complex or simple problems, decision trees have an important place in business. A decision tree is a diagram representation of possible solutions to a decision. It shows different outcomes from a set of decisions.

Decision trees are helpful for a variety of reasons. Not only they are easy-to-understand diagrams that support you ‘see’ your thoughts, but also because they provide a framework for estimating all possible alternatives.

4. Radar Chart

A radar chart is one of the most modern types of charts and cool ways to show data – ideal for multiple comparisons. Radar charts use a circular display with several different quantitative axes looking like spokes on a wheel.

Each axis shows a quantity for a different categorical value. Radar Chart has many applications nowadays in statistics, maths, business, sports analysis, data intelligence, and etc.

5. Cycle Diagram

Cycle diagram is a rarely used method for data visualization and representation. However, it has some interesting benefits and an attractive look. Cycle Diagram shows how one event flows to another.

It presents the steps of a cyclical process or a data flow. Cycle diagrams can be utilized for many different types of processes. For example, you can use Circle diagram to visualize a flow of money in a company or the path of assets that run through a production process.

6. Concept Maps

Concept maps (also known as mind maps) are among the most interesting and cool ways to show data. They are widely used for organizing thoughts, ideas, brainstorming and solving complex business problems.

With the help of a mind map, you can represent and link ideas so you can choose the most critical points and solutions. There are many free mind mapping tools you can use for different purposes.

7. Flowchart

8. Fishbone Diagram

When it comes to creative ways to visualize data, fishbone diagram is definitely one of the best data representing tools. Fishbone diagram is known as one of the key graphical methods to solve business problems because it takes into account all the possible causes.

A fishbone diagram (also known as a cause and effect diagram or Ishikawa diagram) is a visualization tool for categorizing the possible causes of a particular problem or situation. The main goal is to find the root cause. Therefore, it is one of the key root cause analysis tools .

Although it looks difficult for drawing, there are many free  fishbone diagram software tools that make creating Ishikawa diagram a piece of cake.

9. Scatter Plot 

Scatter Plot  can be very interesting and attractive method for representing a relationship between 2 variables.

Scatter Plot is an X-Y diagram that shows a correlation between two variables. It is utilized to plot data points on a vertical and a horizontal axis. The goal is to represent how much one variable affects another.

10. Box and Whisker Plot

Not only their name but also the way they look make you think box and whisker plots are cool ways to show data in statistic or in business.

A box and whisker plot (or just a box plot) is a graph that represents visually data from a five-number summary. These numbers are median, upper and lower quartile, minimum, and maximum data value (extremes).

Don’t panic, these numbers are easy to understand. For more details take a look at our post  box and whisker plot examples .

11. Pie Charts

Pie Charts are a classic way to present data but still, it is one of the coolest and most attractive methods. Pie charts display data and statistics in an easy-to-understand ‘pie-slice’ format and illustrate numerical proportion.

The pie chart brakes down a group into smaller pieces. It shows part-whole relationships. To make a pie chart, you need a list of categorical data and numerical variables.  The total sum of the proportions (pieces) is 100%.

12. Pictographs

The pictograph is one of the most eye-catching ways of showing data in a pictorial form. It displays numerical information with the use of icons or picture symbols to represent data sets.

They are very easy to read statistical way of data visualization. A pictogram shows the frequency of data as images or symbols. Each image/symbol may represent one or more units of a given dataset.

13. Gantt Chart

As a powerful tool at the hands of project managers, Gantt chart is a graphical illustration that represents a project schedule or a timeline. Actually, this is very useful and interesting way of showing tasks displayed against time.

Gantt chart is irreplaceable when it comes to using tools for planning, coordinating, and tracking specific activities in a project.

14. Funnel Chart

Funnel charts are great ways to illustrate stages in a specific process, most common – a sales process. Actually, they could be utilized to show anything that’s decreasing in size.

Funnel charts are very similar to pie charts because the total sum of the bars is 100%. Each funnel stage illustrates a percentage of the whole. Typically, the first stage is the largest, and each next stage is smaller than its predecessor.

15. Pyramid Graph

How to create cool charts and graphs?

The short answer – with the right software tools.

In our high-tech era, there is a wide variety of premium or free graphing software  tools that allow you to create amazing graphs and charts in minutes. They are interesting, visually-appealing, and easy to understand.

Here is a list of the most popular of them:

• FusionCharts

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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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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Data Presentation templates

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What Is Data Visualization?

Data visualization efforts must include the insights received from data, trends and patterns found within the data, as well as a way to discern complex data in a simplified manner. Data visualization comes in two basic forms: static visualization and interactive visualization.

2 Types of Data Visualization

• Static visualization refers to a method of displaying data that tells focuses on only a single data relationship.
• Interactive visualization allow users to select specific data points in order to present findings and create customized visual stories to compare against each other.

Why Is Data Visualization Important?

Data visualization is important for communicating complex business insights and analysis results to all stakeholders in a simplified manner.

Data visualization is a method of understanding and displaying complex data and powerful insights. Strong data visualization allows for better communication with stakeholders throughout an organization, which is crucial to growing a business and capitalizing on new opportunities. The amount of raw enterprise data multiplies yearly and continually presents new information that, when analyzed, can help uncover trends regarding customer behavior, market evolution, overall consumer habits and more.

Data visualization , when preceded by the use of data mining and data modeling techniques, allows analysts to discover vital insights within large data sets. Data visualization helps analysts easily communicate those insights for immediate action.

Related Reading From Built In Experts 7 Ways to Tell Powerful Stories With Your Data Visualization

What Are the 2 Types of Data Visualization?

The two basic types of data visualization are static visualization and interactive visualization.

Static Visualization

Static visualization refers to a method of displaying data that tells a specific story and focuses on only a single data relationship. A common example of static visualization is an engaging single-page layout like an infographic.

Interactive Visualization

Interactive visualizations , for the most part, only exist within software or web applications. This model allows users to select specific data points in order to present findings and create customized visual stories to compare against each other, thereby creating the opportunity for stakeholders to choose from a selection of insights to determine the best path forward, rather than deciding based on a single insight.

Both static and interactive visualization methods present opportunities to display data clearly and accurately. Data analysts should use their best judgment based on the target customer, data story and ROI when deciding on which visualization method to use.

What Are Data Visualization Best Practices?

Some best practices for data visualization include speaking to a specific audience, choosing a proper visualization and providing context.

It is crucial to follow best practices when presenting data visualizations:

• Know Your Audience: Data should always be used to tell a story and uncover trends. It’s vital to know who will be most interested in the information and tailor your visualizations so they can digest the data.
• Choose the Correct Visual: Data visualizations should always present the data in a way that makes it easy to understand. For example, a chart may be the best method of displaying data with a high degree of variability, while graphs may be better for displaying changes in data over time.
• Provide Context: Data without context isn't very helpful, so the data visualizations you choose to put the information in perspective is important. A good visualization will not only show the data is relevant and easily provable, but will also tell a cohesive story.  
• Keep It Simple:  Simple visualizations and dashboards go a long way in data visualization because they allow stakeholders to easily reference data and make informed decisions without becoming confused by the data’s purpose.
• Engage the User: Lastly, engagement is important when presenting complicated data to stakeholders. To prevent users from becoming overwhelmed or intimidated, the overall design and user experience should be graspable without being intimidating.

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Sankey Diagram

Best Practices

An Sankey Diagram is a flow diagram that shows the flow of data across different possible states of the data.  The width of the connections between the states illustrates the volume of data moving to each state.  The volume entering the state matches the flow exiting the state.Usage

A Sankey Diagram is best used to show data movement across a lifecycle or sets of related states.  Select a sankey diagram when:

• Data are best represented when showing how it is divided at each stage of a lifecycle
• You are communicating an overall trend, not specific values

Note on Mobile Display:

In the smallest viewport, the visualization instructs the user to turn their phone to landscape because Sankey diagrams are not really built for vertical phone sizes.

Go To Example

To see a “live” Sankey Diagram, go to the example chart at the bottom of the page.

• Sankey Diagram See key tips and guidelines for working with Sankey Diagrams in the WCMS.
• TP4 UX Best Practices [PPT - 14 MB] For general guidance on colors, layouts, and overall presentation, see this overview of TP4 best practices.

A Sankey Diagram is an interactive content type. In the example below, try selecting and deselecting “story nodes” in the chart.

Example Sankey Diagram

See the sample JSON data file [JSON – 26 KB]  .

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