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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.

“Knowing how to develop and deliver a data-driven presentation is now a crucial skill for many professionals, since we often have to tell our colleagues stories that are much more compelling when they’re backed by numbers,” says researcher and consultant Alexandra Samuel .

No problem, you may say. A bar graph here, and a pie chart there, and you’re off to the races, right?

Not so fast. Because while a good presentation includes data, data alone doesn’t guarantee a good presentation. It’s not the mere presence of data that gives the presenter power. It’s how that data is presented.

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The data-driven mindset.

Showcasing data may seem simple in the age of PowerPoint, Prezi, Canva, Visme, Haiku Deck, and other nonsensically named technological platforms. But raise your hand if you’ve ever been confused by a chart you saw at a conference or ever heard a presenter say, “You probably can’t see this diagram well but what it’s showing is…”? What could be a bigger chart fail than the chart itself being rendered useless?

How you present data can double — or decimate — its impact, so take note of these seven ways to ensure that your data is doing its job.

1) Make sure your data can be seen

This may sound obvious but sometimes you’re too close to your presentation — literally. What is readable on your laptop may be far less so when projected on a screen. Your audience won’t learn what it can’t see. 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. Ask them, “Can you see this chart clearly?” If the answer is anything but a firm “yes,” redesign it to be easier on the eyes.

2) Focus most on the points your data illustrates

In comic book terms, you are Wonder Woman, and data is your magic lasso — a tool that strengthens your impact but has no value until you apply it purposefully. Don’t leave the burden of decoding your data to your audience. It’s your job to explain how the data supports your major points.

“Data slides aren’t really about the data. They’re about the meaning of the data,” explains presentation design expert Nancy Duarte. “It’s up to you to make that meaning clear before you click away. Otherwise, the audience won’t process — let alone buy — your argument.”

When you connect data to the essential points it supports, the transition should be explicit and sound like this:

“This data shows…”

“This chart illustrates…”

“These numbers prove…”

These transitions can be as important as the conclusions themselves, because you’re drawing the audience’s attention to those conclusions.

3) Share one — and only one — major point from each chart

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 keep your charts in check, ask yourself, “What’s the single most important learning I want my audience to extract from this data?” That’s the one learning you should convey. If you have several significant points to make, consider demonstrating each with a new visualization.

The mistake many presenters make is thinking they’re constitutionally required to share every bullet, idea, and data point on a slide. But if you’re sharing a pivotal trend that grew dramatically between 2014 and 2017, what happened in 2013 may be pointless. If 77% of respondents prefer one product and 21% prefer another, what the remaining 2% prefer may also be too insignificant to justify mentioning.

Data-presentation guru Scott Berinato says , “The impulse is to include everything you know, [but] busy charts communicate the idea that you’ve been just that — busy, as in: ‘Look at all the data I have and the work I’ve done.’”

4) Label chart components clearly

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.

Some members of your audience are visual learners (like me!) who process what they see much better than what they hear, so your chart’s visual intuitiveness and clarity are crucial.

5) Visually highlight “Aha!” zones

Every valuable chart or pie graph has an “Aha!” zone — a number or range of data that reveals something crucial to your point.

Smart presenters explain the relevance of the “Aha!” zone orally, sharing the learning, trend, or story the data is telling.

Better presenters explain it out loud, but also write it on the slide as a bullet.

But the best presenters do all of the above AND visually highlight the “Aha!” zone itself with a circle or shading to reach the differentiated (aural, verbal, visual) learners in their audience, as well as to triple-reinforce the most important data takeaways.

6) Write a slide title that reinforces the data’s point

Even when data is presented effectively on a slide, the most valuable real estate is the page’s title because that’s the first item the audience will notice and process. But all too often, presenters use generic words and phrases like “Statistics” and “By the Numbers” that serve no functional purpose.

Even when the titles are specific, like “Millennial Preferences” or “Campaign Awareness,” they can still be elevated with more point-specific titles like “Millennials Prefer Mobile” or “Campaign Awareness is Increasing.”

7) Present to your audience, not to your data

Many presenters look at their slides while they share data as if the PowerPoint is their audience. But only your audience is your audience, and, as fellow human beings, they receive your points best when you look them in the eye. This doesn’t mean that you should never look at your data — just don’t have a conversation with it. Glance at your slides for reference, but make critical points directly to your audience.

When presented clearly and pointedly, data can elevate your point’s credibility and trustworthiness. Presenting data poorly not only squanders that opportunity but can damage your reputation as a presenter. Like Wonder Woman’s lasso, it’s a powerful tool to draw out compelling truths — wield it wisely.

• 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 on Twitter  @TheJoelTruth.

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How to Present Data Effectively

You’re sitting in front of your computer and ready to put together a presentation involving data.   The numbers stare at you from your screen, jumbled and raw.   How do you start?   Numbers on their own can be difficult to digest. Without any context, they’re just that—numbers.   But organize them well and they tell a story.   In this blog post, we’ll go into the importance of structuring data in a presentation and provide tips on how to do it well. These tips are practical and applicable for all sorts of presentations—from marketing plans and medical breakthroughs to project proposals and portfolios. 

What is data presentation?

3 essential tips on data presentation, use the right chart, keep it simple, use text wisely and sparingly.

In many ways, data presentation is like storytelling—only you do them with a series of graphs and charts.  One of the most common mistakes presenters make is being so submerged in the data that they fail to view it from an outsider’s point of view.   Always keep this in mind: What makes sense to you may not make sense to your audience. To portray figures and statistics in a way that’s comprehensible to your viewers, step back, put yourself in their shoes, and consider the following: 

• How much do they know about the topic?
• How much information will they need?
• What data will impress them?

Providing a context helps your audience visualize and understand the numbers. To help you achieve that, here are three tips on how to represent data effectively.  

Whether you’re using Google Slides or PowerPoint, both come equipped with a range of design tools that help you help your viewers make sense of your qualitative data.  The key here is to know how to use them and how to use them well. In these tips, we’ll cover the basics of data presentation that are often overlooked but also go beyond basics for more professional advice. 

The downside of having too many tools at your disposal is that it makes selecting an uphill task.   Pie and bar charts are by far the most commonly used methods as they are versatile and easy to understand. 

If you’re looking to kick things up a notch, think outside the box. When the numbers allow for it, opt for something different. For example, donut charts can sometimes be used to execute the same effect as pie charts. 

But these conventional graphs and charts aren’t applicable to all types of data. For example, if you’re comparing numerous variables and factors, a bar chart would do no good. A table, on the other hand, offers a much cleaner look.

Pro tip : If you want to go beyond basics, create your own shapes and use their sizes to reflect proportion, as seen in this next image.

Their sizes don’t have to be an exact reflection of their proportions. What’s important here is that they’re discernible and are of the same shape so that your viewers can grasp its concept at first glance.  Note that this should only be used for comparisons with large enough contrasts. For instance, it’d be difficult to use this to compare two market sizes of 25 percent and 26 percent. 

When it comes to making qualitative data digestible, simplicity does the trick.  Limit the number of elements on the slide as much as possible and provide only the bare essentials. 

See how simple this slide is? In one glance, your eye immediately goes to the percentages of the donut because there are no text boxes, illustrations, graphics, etc. to distract you.  Sometimes, more context is needed for your numbers to make sense. In the spirit of keeping your slides neat, you may be tempted to spread the data across two slides. But that makes it complicated, so putting it all on one slide is your only option.  In such cases, our mantra of “keep it simple” still applies. The trick lies in neat positioning and clever formatting.  

In the above slides, we’ve used boxes to highlight supporting figures while giving enough attention to the main chart. This separates them visually and helps the audience focus better.  With the slide already pretty full, it’s crucial to use a plain background or risk overwhelming your viewers.  

Last but certainly not least, our final tip involves the use of text.  Just because you’re telling a story with numbers doesn’t mean text cannot be used. In fact, the contrary proves true: Text plays a vital role in data presentation and should be used strategically.  To highlight a particular statistic, do not hesitate to go all out and have that be the focal point of your slide for emphasis. Keep text to a minimum and as a supporting element. 

Make sure your numbers are formatted clearly. Large figures should have thousands separated with commas. For example, 4,498,300,000 makes for a much easier read than “4498300000”. Any corresponding units should also be clear.  With data presentation, don’t forget that numbers are still your protagonist, so they must be highlighted with a larger or bolder font.  Where there are numbers and graphics, space is scarce so every single word must be chosen wisely.   The key here is to ensure your viewers understand what your data represents in one glance but to leave it sufficiently vague, like a teaser, so that they pay attention to your speech for more information.  → Slidesgo’s free presentation templates come included with specially designed and created charts and graphs that you can easily personalize according to your data. Give them a try now! 

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10 Methods of Data Presentation with 5 Great Tips to Practice, Best in 2023

Leah Nguyen • 24 May 2023 • 10 min read

Finding ways to present information effectively? 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

#2 – Text

#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

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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.

#1 – Tabular 

Tabular data is 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. 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 a histogram to see which score group most of the students fall into, like in this example above.

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. 

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.

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 and Q&A sections 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

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.

What are the Best Methods of Data Presentation?

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👇

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What is chart presentation?

When can i use charts for presentation, why should use charts for presentation, what are the 4 graphical methods of presenting data.

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A former event organiser on the ultimate quest - to help presenters create the juiciest online experiences and leave all attendees on a high note.

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Presentation of Data

Data Presenting for Clearer Reference

Imagine the statistical data without a definite presentation, will be burdensome! Data presentation is one of the important aspects of Statistics. Presenting the data helps the users to study and explain the statistics thoroughly. We are going to discuss this presentation of data and know-how information is laid down methodically. 

In this context, we are going to present the topic - Presentation of Data which is to be referred to by the students and the same is to be studied in regard to the types of presentations of data. 

Presentation of Data and Information

Statistics is all about data. Presenting data effectively and efficiently is an art. You may have uncovered many truths that are complex and need long explanations while writing. This is where the importance of the presentation of data comes in. You have to present your findings in such a way that the readers can go through them quickly and understand each and every point that you wanted to showcase. As time progressed and new and complex research started happening, people realized the importance of the presentation of data to make sense of the findings.

Define Data Presentation

Data presentation is defined as the process of using various graphical formats to visually represent the relationship between two or more data sets so that an informed decision can be made based on them.

Types of Data Presentation

Broadly speaking, there are three methods of data presentation:

Diagrammatic

Textual Ways of Presenting Data

Out of the different methods of data presentation, this is the simplest one. You just write your findings in a coherent manner and your job is done. The demerit of this method is that one has to read the whole text to get a clear picture. Yes, the introduction, summary, and conclusion can help condense the information.

Tabular Ways of Data Presentation and Analysis

To avoid the complexities involved in the textual way of data presentation, people use tables and charts to present data. In this method, data is presented in rows and columns - just like you see in a cricket match showing who made how many runs. Each row and column have an attribute (name, year, sex, age, and other things like these). It is against these attributes that data is written within a cell.

Diagrammatic Presentation: Graphical Presentation of Data in Statistics

This kind of data presentation and analysis method says a lot with dramatically short amounts of time.

Diagrammatic Presentation has been divided into further categories:

Geometric Diagram

When a Diagrammatic presentation involves shapes like a bar or circle, we call that a Geometric Diagram. Examples of Geometric Diagram

Bar Diagram

Simple Bar Diagram

Simple Bar Diagram is composed of rectangular bars. All of these bars have the same width and are placed at an equal distance from each other. The bars are placed on the X-axis. The height or length of the bars is used as the means of measurement. So, on the Y-axis, you have the measurement relevant to the data. 

Suppose, you want to present the run scored by each batsman in a game in the form of a bar chart. Mark the runs on the Y-axis - in ascending order from the bottom. So, the lowest scorer will be represented in the form of the smallest bar and the highest scorer in the form of the longest bar.

Multiple Bar Diagram

(Image will be uploaded soon)

In many states of India, electric bills have bar diagrams showing the consumption in the last 5 months. Along with these bars, they also have bars that show the consumption that happened in the same months of the previous year. This kind of Bar Diagram is called Multiple Bar Diagrams.

Component Bar Diagram

(image will be uploaded soon)

Sometimes, a bar is divided into two or more parts. For example, if there is a Bar Diagram, the bars of which show the percentage of male voters who voted and who didn’t and the female voters who voted and who didn’t. Instead of creating separate bars for who did and who did not, you can divide one bar into who did and who did not.

A pie chart is a chart where you divide a pie (a circle) into different parts based on the data. Each of the data is first transformed into a percentage and then that percentage figure is multiplied by 3.6 degrees. The result that you get is the angular degree of that corresponding data to be drawn in the pie chart. So, for example, you get 30 degrees as the result, on the pie chart you draw that angle from the center.

Frequency Diagram

Suppose you want to present data that shows how many students have 1 to 2 pens, how many have 3 to 5 pens, how many have 6 to 10 pens (grouped frequency) you do that with the help of a Frequency Diagram. A Frequency Diagram can be of many kinds:

Where the grouped frequency of pens (from the above example) is written on the X-axis and the numbers of students are marked on the Y-axis. The data is presented in the form of bars.

Frequency Polygon

When you join the midpoints of the upper side of the rectangles in a histogram, you get a Frequency Polygon

Frequency Curve

When you draw a freehand line that passes through the points of the Frequency Polygon, you get a Frequency Curve.

Ogive 

Suppose 2 students got 0-20 marks in maths, 5 students got 20-30 marks and 4 students got 30-50 marks in Maths. So how many students got less than 50 marks? Yes, 5+2=7. And how many students got more than 20 marks? 5+4=9. This type of more than and less than data are represented in the form of the ogive. The meeting point of the less than and more than line will give you the Median.

Arithmetic Line Graph

If you want to see the trend of Corona infection vs the number of recoveries from January 2020 to December 2020, you can do that in the form of an Arithmetic Line Graph. The months should be marked on the X-axis and the number of infections and recoveries are marked on the Y-axis. You can compare if the recovery is greater than the infection and if the recovery and infection are going at the same rate or not with the help of this Diagram.

Did You Know?

Sir Ronald Aylmer Fisher is known as the father of modern statistics.

FAQs on Presentation of Data

1. What are the 4 types of Tabular Presentation?

The tabular presentation method can be further divided into 4 categories:

Qualitative

Quantitative

Qualitative classification is done when the attributes in the table are some kind of ‘quality’ or feature. Suppose you want to make a table where you would show how many batsmen made half-centuries and how many batsmen made centuries in IPL 2020. Notice that the data would have only numbers - no age, sex, height is needed. This type of tabulation is called quantitative tabulation.

If you want to make a table that would inform which year’s world cup, which team won. The classifying variable, here, is year or time. This kind of classification is called Temporal classification.

If you want to list the top 5 coldest places in the world. The classifying variable here would be a place in each case. This kind of classification is called Spatial Classification.

2. Are bar charts and histograms the Same?

No, they are not the same. With a histogram, you measure the frequency of quantitative data. With bar charts, you compare categorical data.

3. What is the definition of Data Presentation?

When research work is completed, the data gathered from it can be quite large and complex. Organizing the data in a coherent, easy-to-understand, quick to read and graphical way is called data presentation.

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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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Top 5 Easy-to-Follow Data Presentation Examples

You’ll agree when we say that poring through numbers is tedious at best and mentally exhausting at worst.

And this is where data presentation examples come in.

Charts come in and distill data into meaningful insights. And this saves tons of hours, which you can use to relax or execute other tasks. Besides, when creating data stories, you need charts that communicate insights with clarity.

There’re 5 solid and reliable data presentation methods: textual, statistical data presentation, measures of dispersion, tabular, and graphical data representation.

Besides, some of the tested and proven charts for data presentation include:

• Double Bar Graph
• Slope Chart
• Treemap Charts
• Radar Chart
• Sankey Chart

There’re visualization tools that produce simple, insightful, and ready-made data presentation charts. Yes, you read that right. These tools create charts that complement data stories seamlessly.

Remember, without visualizing data to extract insights, chances of creating a compelling narrative will go down.

Table of Content:

What is data presentation, top 5 data presentation examples:, how to generate sankey chart in excel for data presentation, importance of data presentation in business, benefits of data presentation, what are the top 5 methods of data presentation.

Data presentation is the process of using charts and graphs formats to display insights into data. The insights could be:

• Relationship
• Trend and patterns

Data Analysis  and  Data Presentation  have a practical implementation in every possible field. It can range from academic studies, commercial, industrial , and marketing activities to professional practices .

In its raw form, data can be extremely complicated to decipher. Data presentation examples are an important step toward breaking down data into understandable charts or graphs.

You can use tools (which we’ll talk about later) to analyze raw data.

Once the required information is obtained from the data, the next logical step is to present the data in a graphical presentation.

The presentation is the key to success.

Once you’ve extracted actionable insights, you can craft a compelling data story. Keep reading because we’ll address the following in the coming section: the importance of data presentation in business.

Let’s take a look at the five data presentation examples below:

1. Double Bar Graph

A Double Bar Chart displays more than one data series in clustered horizontal columns.

Each data series shares the same axis labels, so horizontal bars are grouped by category.

Bars directly compare multiple series in a given category. The chart is amazingly easy to read and interpret, even for a non-technical audience.

2. Slope Chart

Slope Charts are simple graphs that quickly and directly show  transitions, changes over time, absolute values, and even rankings .

Besides, they’re also called Slope Graphs.

This is one of the data presentation examples you can use to show the before and after story of variables in your data.

Slope Graphs can be useful when you have two time periods or points of comparison and want to show relative increases and decreases quickly across various categories between two data points.

Take a look at the table below. Can you provide coherent and actionable insights into the table below?

Notice the difference after visualizing the table. You can easily tell the performance of individual segments in:

• Macy’s Store

4. Radar Chart

Radar Chart is also known as Spider Chart or Spider Web Chart. A radar chart is very helpful to visualize the comparison between multiple categories and variables.

A radar Chart is one of the data presentation examples you can use to compare data of two different time ranges e.g. Current vs Previous. Radar Chart with different scales makes it easy for you to identify trends, patterns, and outliers in your data. You can also use Radar Chart to visualize the data of Polar graph equations.

5. Sankey Chart

You can use Sankey Chart to visualize data with flow-like attributes, such as material, energy, cost, etc.

This chart draws the reader’s attention to the enormous flows, the largest consumer, the major losses , and other insights.

The aforementioned visualization design is one of the data presentation examples that use links and nodes to uncover hidden insights into relationships between critical metrics.

The size of a node is directly proportionate to the quantity of the data point under review.

So how can you access the data presentation examples (highlighted above)?

Excel is one of the most used tools for visualizing data because it’s easy to use. 

However, you cannot access ready-made and visually appealing data presentation charts for storytelling. But this does not mean you should ditch this freemium data visualization tool.

Did you know you can supercharge your Excel with add-ins to access visually stunning and ready-to-go data presentation charts?

Yes, you can increase the functionality of your Excel and access ready-made data presentation examples for your data stories.

The add-on we recommend you to use is ChartExpo.

What is ChartExpo?

We recommend this tool (ChartExpo) because it’s super easy to use.

You don’t need to take programming night classes to extract insights from your data. ChartExpo is more of a ‘drag-and-drop tool,’ which means you’ll only need to scroll your mouse and fill in respective metrics and dimensions in your data.

ChartExpo comes with a 7-day free trial period.

The tool produces charts that are incredibly easy to read and interpret . And it allows you to save charts in the world’s most recognized formats, namely PNG and JPG.

In the coming section, we’ll show you how to use ChartExpo to visualize your data with one of the data presentation examples (Sankey).

  To install ChartExpo add-in into your Excel, click this link .

• Open your Excel and paste the table above.
• Click the My Apps button.

• Then select ChartExpo and click on  INSERT, as shown below.

• Click the Search Box and type “Sankey Chart” .

• Once the chart pops up, click on its icon to get started.

• Select the sheet holding your data and click the Create Chart from Selection button.

How to Edit the Sankey Chart?

• Click the Edit Chart button, as shown above.

• Once the Chart Header Properties window shows, click the Line 1 box and fill in your title.

• To change the color of the nodes, click the pen-like icons on the nodes.
• Once the color window shows, select the Node Color and then the Apply button.

• Save your changes by clicking the Apply button.
• Check out the final chart below.

Data presentation examples are vital, especially when crafting data stories for the top management. Top management can use data presentation charts, such as Sankey, as a backdrop for their decision.

Presentation charts, maps, and graphs are powerful because they simplify data by making it understandable & readable at the same time. Besides, they make data stories compelling and irresistible to target audiences.

Big files with numbers are usually hard to read and make it difficult to spot patterns easily. However, many businesses believe that developing visual reports focused on creating stories around data is unnecessary; they think that the data alone should be sufficient for decision-making.

Visualizing supports this and lightens the decision-making process.

Luckily, there are innovative applications you can use to visualize all the data your company has into dashboards, graphs, and reports. Data visualization helps transform your numbers into an engaging story with details and patterns.

Check out more benefits of data presentation examples below:

1. Easy to understand

You can interpret vast quantities of data clearly and cohesively to draw insights, thanks to graphic representations.

Using data presentation examples, such as charts, managers and decision-makers can easily create and rapidly consume key metrics.

If any of the aforementioned metrics have anomalies — ie. sales are significantly down in one region — decision-makers will easily dig into the data to diagnose the problem.

2. Spot patterns

Data visualization can help you to do trend analysis and respond rapidly on the grounds of what you see.

Such patterns make more sense when graphically represented; because charts make it easier to identify correlated parameters.

3. Data Narratives

You can use data presentation charts, such as Sankey, to build dashboards and turn them into stories.

Data storytelling can help you connect with potential readers and audiences on an emotional level.

4. Speed up the decision-making process

We naturally process visual images 60,000 times faster than text. A graph, chart, or other visual representation of data is more comfortable for our brain to process.

Thanks to our ability to easily interpret visual content, data presentation examples can dramatically improve the speed of decision-making processes.

Take a look at the table below?

Can you give reliable insights into the table above?

Keep reading because we’ll explore easy-to-follow data presentation examples in the coming section. Also, we’ll address the following question: what are the top 5 methods of data presentation?

1. Textual Ways of Presenting Data

Out of the five data presentation examples, this is the simplest one.

Just write your findings coherently and your job is done. The demerit of this method is that one has to read the whole text to get a clear picture.  Yes, you read that right.

The introduction, summary, and conclusion can help condense the information.

2. Statistical data presentation

Data on its own is less valuable. However, for it to be valuable to your business, it has to be:

No matter how well manipulated, the insights into raw data should be presented in an easy-to-follow sequence to keep the audience waiting for more.

Text is the principal method for explaining findings, outlining trends, and providing contextual information. A table is best suited for representing individual information and represents both quantitative and qualitative information.

On the other hand, a graph is a very effective visual tool because:

• It displays data at a glance
• Facilitates comparison
• Reveals trends, relationships, frequency distribution, and correlation

Text, tables, and graphs are incredibly effective data presentation examples you can leverage to curate persuasive data narratives.

3. Measure of Dispersion

Statistical dispersion is how a key metric is likely to deviate from the average value. In other words, dispersion can help you to understand the distribution of key data points.

There are two types of measures of dispersion, namely:

• Absolute Measure of Dispersion
• Relative Measure of Dispersion

4. Tabular Ways of Data Presentation and Analysis

To avoid the complexities associated with qualitative data, use tables and charts to display insights.

This is one of the data presentation examples where values are displayed in rows and columns. All rows and columns have an attribute (name, year, gender, and age).

5. Graphical Data Representation

Graphical representation uses charts and graphs to visually display, analyze, clarify, and interpret numerical data, functions, and other qualitative structures.

Data is ingested into charts and graphs, such as Sankey, and then represented by a variety of symbols, such as lines and bars.

Data presentation examples, such as Bar Charts , can help you illustrate trends, relationships, comparisons, and outliers between data points.

What is the main objective of data presentation?

Discovery and communication are the two key objectives of data presentation.

In the discovery phase, we recommend you try various charts and graphs to understand the insights into the raw data. The communication phase is focused on presenting the insights in a summarized form.

What is the importance of graphs and charts in business?

Big files with numbers are usually hard to read and make it difficult to spot patterns easily.

Presentation charts, maps, and graphs are vital because they simplify data by making it understandable & readable at the same time. Besides, they make data stories compelling and irresistible to target audiences.

Poring through numbers is tedious at best and mentally exhausting at worst.

This is where data presentation examples come into play.

Charts come in and distill data into meaningful insights. And this saves tons of hours, which you can use to handle other tasks. Besides, when creating data stories, it would be best if you had charts that communicate insights with clarity.

Excel, one of the popular tools for visualizing data, comes with very basic data presentation charts, which require a lot of editing.

We recommend you try ChartExpo because it’s one of the most trusted add-ins. Besides, it has a super-friendly user interface for everyone, irrespective of their computer skills.

Create simple, ready-made, and easy-to-interpret Bar Charts today without breaking a sweat.

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5 Tips For Better Data Presentation

Home >  Presenting Data Main >  5 Data Presentation Tips

Most data presentations are confusing and boring. Learn the 5 tips to make your presentation clearer and more memorable.

Tip 1: Put your conclusion on the title

Most presenters use vague slide titles like Our Sales Performance. This doesn’t give the audience any clue about what to look for in the sea of numbers presented on the slide.

Always put the conclusion from your slide on the slide title. Since your audience naturally scan your slides top down, a clear title helps them find your key message fast.

See this table of data on a slide:

Since the conclusion is clearly mentioned on the title, audience’s eyes are naturally led to the relevant numbers on the table.

Tip 2: Highlight your inference

A lot of presenters lose their audience because they make them think. They expect their audience to do mental math and draw their own conclusions. Since most audiences prefer to switch off than to process complex information, data presentation gets quite tricky.

Realize that not everyone in your audience likes to crunch numbers. Most of them expect you to do the math and tell them the inference. Highlight the inference so clearly that there is no scope for confusion for your audience.

See the PowerPoint slide with clear graph below:

The areas that depict losses and profits are highlighted clearly in different colors.

All that is left for the audience to do is to read the conclusion on the title and see the proof (assertion-evidence method)  in the body of the slide to move forward.

Tip 3: Use images to make your message more memorable

Sometimes in a data presentation, numbers can be cold and intimidating. Using relevant images can make your information more inviting.

See the following slide with map showing data:

The picture of the world map helps the audience get a visual context for the 4 pie charts. Every time you put up some numbers on the slide, think about adding a relevant picture to add clarity to your message.

Tip 4: Use visual representation of numbers

You can make your column charts and pie charts come to life by using small icons to act as units for your chart.

For example, take a look at this column chart:

See Related Data-Driven PowerPoint Pictographs from Visual Graphs Pack

All we did was to copy a cardboard box and paste it multiple times one over the other. The chart got ready in seconds. You may copy-paste small icons specific to your industry to make your chart visual.

You don’t need to limit yourself to icons. Think about using other images to serve as visual clue for your numbers.

For example, take a look at this creative slide:

Related Data Driven Dials Showing Completion from Visual Graphs Pack

We used the picture of a clock and shaded the relevant portion to make our point. A clock makes it easier to visualize 15 minutes better than words. You can think of more creative ways of presenting data.

Tip 5: Present information in stages

Make it a habit to animate your charts before presenting them. It makes your numbers less intimidating and helps your audiences get more information from your charts.

In the following example, see how we present data in stages:

First the axes are explained. Then line graph of Product X is shown to make the base case. This is then followed by the line graph of Product Y. This helps the audience realize how the sales of Product Y fluctuates more than the sales of Product X.

If you are not aware of chart animation feature of PowerPoint, here is a quick tutorial of how it is done.

PowerPoint Chart Animation Feature

First select the chart you imported from excel file. Go to animations -> Custom animation and select the kind of animation you want to use. This animates the whole chart.

Then, go to the custom animation menu and click on the drop down arrow next to the animation you selected. Go to Effect options and you will see a pop up box which gives you the option to choose chart animation.

You can animate your chart by Series or by category. This is extremely helpful to make effective data presentations.

Summary of 5 tips for better data presentation:

• Put your conclusion on the title
• Highlight your inference
• Use images to make your message more memorable
• Use visual representation of numbers
• Present information in stages

These tips make your data presentation effective and memorable.

Easy Option for Business Presenters:

Our Data-Driven PowerPoint Graphs Pack is an easy option for busy presenters. We have done all the hard work for you. The pack has everything from regular charts like bar, pie, line charts to unique and creative data-driven infographics to help you get across your business information easily.

Take a look at some of the pre-formatted templates from the Graphs pack here

Waterfall Charts with Brick Style Blocks from Graphs Pack

Yes and No Charts & Butterfly Charts

Jaws Chart Showing Performance Comparison Across Products

These graphs are surprisingly easy to use and don’t require any additional software or extensive PowerPoint knowledge. You just need to copy our graphs to your slides and replace your data in the worksheet.

It is so easy to present insights to audience with such graphs.You can now do away with confusing excel sheets and tables. Please do browse through the gallery of 320+ high-quality graphs for business presenters here  >>

Related Article: Presentation on 3 Myths about Presenting Data

Related Article: 5 Examples of Visual Presentations using Analogy

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