12 Data Visualization Techniques for Professionals | 2024 Guide (2024)

We live in a data-driven society. If you want to succeed, you need to be able to understand and communicate data effectively.

Properly used visual aids can help others understand your data at a glance and can assist you in making more informed choices.

In this article, you’ll learn some of the most effective data visualization techniques, how to use them and how to create them easily.

Here are 12 techniques to create professional data visuals.

12 Data Visualization Techniques for Professionals

• Technique #1: Consider Your Audience
• Technique #2: Choose the Right Data Visualization Tools
• Technique #3: Choose Appropriate Charts and Graphs
• Technique #4: Use Multiple Charts to Visualize Big Data
• Technique #5: Use Color to Convey Meaning
• Technique #6: Use 3D Assets
• Technique #7: Incorporate Thematic Design
• Technique #8: Add Motion and Interactive Elements
• Technique #9: Limit Your Text
• Technique #10: Use Size and Placement to Your Advantage
• Technique #11: Leverage Cross-Platform Integrations
• Technique #12: Share With Others
• Data Visualization FAQs

Technique #1: Consider Your Audience

The whole purpose of communication is to convey your ideas and findings to other people. As a communicator, it's your job to make sure your material is appropriate for your audience.

Humans are visual learners by nature, which is why visual aids like data visualization can help your audience grasp important information in your presentation.

Graphs and charts not only convey metrics and data points, but also make it easier to spot patterns, trends and outliers in data sets with the help of colors, lines and shapes.

When considering your audience, avoid overpopulating your presentations with oversized data visuals. It may also help to cut out data visuals of things that are considered common knowledge, and save the extra space for better and more concise visual elements.

If your audience sees an overpopulation of charts and graphs with difficult-to-follow lines, they will check out mentally and not focus on the material at hand.

Take some time and consider who will be interacting with your presentation. Then, carefully choose what pieces of information could benefit from graphical representation.

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Choosing the correct data visualization tools is a vital decision for any job. In fact, it’s one of the most critical techniques of data visualization.

Having quality tools can have a huge impact on your final product, as well as determine the kind of experience you'll have as a user.

When it comes to creating professional data visualization presentations, charts and graphs, videos, infographics and more, Visme is the trusted online design platform for the job.

Visme has every tool an online marketer and marketing team could ever need for creating content. It offers 30+ data widgets and 20+ types of charts, graphs, maps and other data visualization tools that you can add to your project.

Instead of paying a pretty penny for each tool individually, why not just use one workspace with all the tools in one place for you and your team?

Visme also allows you to import your pre-existing data from places like Survey Monkey, Google Sheets, Microsoft Excel and more directly into your projects. The data will then be automatically updated to fit the chart or graph you choose. Visme does all the data work for you.

From creating short animated videos for social media platforms to creating an in-depth data analysis presentation for potential investors, Visme has you covered.

Technique #3: Choose Appropriate Charts and Graphs

Not every graph is suitable for all kinds of data. The data visualization type you choose should depend on the nature of your data and how easy it is for your audience to read it.

For example, look at this pie chart and try to guess the order from largest to smallest.

Pretty difficult right?

If your chart or graph does not clearly communicate your point, try using a different data visualization methods.

Try using a histogram or bar chart when comparing the difference between data sets. Bar graphs are a great and easy-to-understand way to compare two or more data sets.

For data analytics with larger variations in a sample set, consider using a line chart, scatter plot or even box plots.

Visme has hundreds of professionally designed tables, charts and graphs to help you as you prepare to present data. These charts and graphs update the slides in real-time as you enter your data into the app.

The moral of the story is that not every business presentation needs pie charts and bar graphs. Maybe a line graph or a scatter plot would work better for you. Or, maybe, all you need are some data widgets like radials and progress bars to visualize percentages.

Take some time to look through the different types of data visualization assets at your disposal and think through how your audience will perceive the presented data.

Here’s a list of some commonly used data visualization types to choose from:

• Pie Chart
• Bar Graph
• Histogram
• Bubble Chart
• Gantt Chart
• Heat Map
• Box and Whisker Plot
• Waterfall Chart
• Area Chart
• Scatter Plot
• Pictogram Chart
• Mekko Chart
• Dual Charts
• Polar Area Charts

Technique #4: Use Multiple Charts to Visualize Big Data

“Kiss - keep it simple stupid”.

You can apply this rule to multiple areas of life, including data visualization. Some people get too excited when creating a graph and try to cram everything into one single chart.

Incorporating too many visual elements into one graph will make your data difficult to understand. Not everything has to fit in one graph. Consider breaking up your data into smaller and more digestible pieces.

Charts that give too much information in one image may overwhelm your audience and cause them to lose interest in the subject matter.

Presenting large data sets does not always require a big chart. Consider using a variety of smaller charts to explain big ideas. Take a look at the example below:

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By utilizing multiple chart types and having a cleaner distribution of data, you're able to more clearly present the same ideas from the same data sources.

You don't need to be a professional data analyst to see what's going on in the example above. That is exactly how we want our charts to look.

Visme has professional data visualization templates ready for you to use. All you have to do is simply plug in your data and we’ll take care of the exciting design for you.

When your ideas have a clear visual representation, your audience is more likely to be engaged.

Technique #5: Use Color to Convey Meaning

To truly make your presentation look professional and presentable, you should pick a color scheme and stick with it.

Make sure your colors do not “clash” together to create bad contrast. Here's an example of a good vs. bad color scheme used in data visualization.

Instead of randomly selecting colors, try using analogous and complementary colors.

Analogous colors are colors that are neighboring one another on the standard color wheel. Complementary colors are colors from the opposite side of the color wheel.

At first glance, complementary and analogous colors may not seem to go well together. Try turning down the saturation on your color selection. This will make the colors less vibrant and bold, and give off a less abrasive feel.

Complementary colors are used to make a strong contrast between two things. If you want an object to jettison off the page, try using the complementary colors of your choice.

If you have similar data types and want to present an overarching theme of that data using color, try using analogous colors.

Does that sound confusing? Don’t worry. Visme has preset color themes created by professional designers that take the guesswork out of choosing colors for your presentation.

Click on a preset theme you like to change the color scheme of your entire presentation in one go. You can also flip back and forth between the different color schemes to see which one looks best.

Play around with it until you have your desired color scheme and viola—you have the presentation of a professional designer.

Another important fact to keep in mind when selecting colors is that humans are conditioned to associate colors with feelings. For example, red tends to mean stop, heat or danger, while green tends to indicate growth, movement or peace.

For a practical illustration, imagine you are making a heat map of the average temperature of the United States. You would naturally associate red with heat and blue or green with coolness. It would be ill-advised to use red to represent a clear forecast and good weather.

While this data visualization technique may seem obvious, you would be surprised by how many people neglect it in their visual designs.

Keep your projects on brand with Visme’s brand wizard. Just input your URL and the tool will pull up your brand assets and save them to your brand kit. The tool also recommends beautiful templates for your business based on your branding.

Next to this, there are so many other techniques you can incorporate into your data visualization. As you go further into the article, you’ll begin to see various data visualization techniques that you might have overlooked in the past.

Technique #6: Use 3D assets

Why not add a bit more depth to your data? 3D (three-dimensional) graphs are multidimensional graphs that give your graph an X, Y and Z-axis.

This technique makes your two-dimensional visuals appear to have depth and can cause certain parts of the page to “pop out.”

Here's an example of a 3D bar graph template:

Utilizing 3D assets can really help your graphs and charts stand out from the crowd and leave a lasting impression in people's minds.

Generally, rendering 3D assets would take a top-of-the-line computer with the fastest CPU, excessive amounts of RAM, a very strong GPU and software that costs thousands of dollars.

However, with cloud-based design software like Visme, you can now have access to high-quality 3D rendered assets that update in real-time on your phone and across all of your devices!

Technique #7: Incorporate Thematic Design

Incorporating graphics related to your overall theme can help your audience remember the presented material or push people toward making a commitment.

In this example, you may notice the use of icons as a form of data visualization.

While the designer could have used a line graph or an area chart to show the exact number of people without water, there's something more visually telling about this simple design.

Incorporating thematically appropriate graphic design elements into your slides makes your presentation more relatable. By doing so, you can push your audience into a decision-making state of mind and present your call to action.

You can use any icon that goes well with your overall theme as a representation of data.

Typically, you would mostly want to do this with your top data points, as it would be impractical to expect every numerical value to be replaced with icons and graphic design elements.

With that said, don't be afraid to experiment with different ways to represent your data.

Technique #8: Add Motion and Interactive Elements

Did you know that the human eye prioritizes the detection of motion over color? Our ancestors used this skill to track and hunt animals long ago and now we are left with the residual effects.

In order to captivate your audience's attention, you should add a bit of motion into your presentation and data visuals.

If you are using a chart as your big data visualization, consider adding an animation to draw your listener’s attention to this data piece.

Visme makes this process easy with tons of graph templates to choose from that are automatically animated. You can also add motion to data visuals as you go through your presentation.

This makes effective visualization of your data near-effortless!

Like all good things in life, use motion sparingly and only on the important bits of presentation. If you use too much motion at once, your viewers will not know where to look and may become overwhelmed with an abundant amount of motion.

To further increase engagement, you can make your data interactive. You can create enter and exit effects for graphic elements and time them to appear based on user interactions or at specific intervals. Or create personalized pop-ups that reveal additional information when users hover over or click on specific elements.

Technique #9: Limit Your Text

This may sound counter-intuitive but hear me out. The secret to good data visuals and descriptive statistics is to use fewer words, rather than too many.

For a period of time, it was believed by many PowerPoint users that the more text you cram onto your visual, the better.

That is statistically and experimentally not true.

While it is important to include labels, it is equally important to let your graphical display speak for itself. Here's an example of data visualization template that uses minimal text:

Our brains are predisposed to analyze patterns, icons and visuals over words, so try using text only where it matters most. In the example above, the only large text is the initial label and the numerical value next to the horizontal bars.

It is far better to let the visuals speak for themselves or let the presenter speak, rather than to cram microscopic and illegible text onto the visuals.

If you're going to use text, make sure it is used to highlight necessary details, such as the information along the x-axis and the y-axis of a line graph.

In most cases, you want to limit your text. One of the visualization types that is an exception to this rule is a word cloud.

Technique #10: Use Size and Placement to Your Advantage

When visualizing data, it is important to make the visual large enough to be legible and visually pleasing to look at.

Because our aim is to communicate data via visual means, it is important for our data to be “easy on the eyes” and aesthetically pleasing.

As was mentioned earlier, it is important to break down complex data points into smaller, digestible visuals. You can change the size of these visuals to convey importance or chronological order.

Generally speaking, the size of the graph is proportional to the amount of importance placed on a piece of data.

Do not think you have to divide your visual into 4 equal quartile pieces. Take some time to adjust the size of your graph for emphasis’s sake and not just legibility.

Placement is also another way to convey importance.

Place your larger, more important design elements near the top or in the upper left corner. Our attention is drawn to that spot first.

Play around with the placement a bit until you find your desired location for an element on your design.

Let's imagine a company is going through its key performance indicators (KPIS) and the presenter wants to emphasize major success or failures.

The way the presenter utilizes size, color and placement of that data in their infographic will all play a factor in the effectiveness of communicating its importance.

If the least important data is the largest piece of data displayed, the viewer's eyes will naturally be drawn to what is not important.

If the presenter wants to be effective in their communication, they should utilize proper size, placement and order.

Unstructured data is not visually appealing and may not effectively communicate your main data points to your audience.

Visme’s software has a guide placement system in place to help you properly align your visuals, so you can create a well-balanced visual aid.

Technique #11: Leverage Cross-Platform Integrations

If you need to finish your data visuals within an allotted time period, it is important that you are able to work on your presentations wherever you go and with whatever technology you have on hand.

Let’s say you have a supercomputer at the office, but a computer that is over a decade old at home.

If you wanted to work on your project from home, your computer might not have the power to run the algorithms most content-creation software needs in order to function correctly.

Even the latest and greatest cell phones cannot run some of the best software. This is why it is important to use a cloud-based service for rendering your data visuals.

Visme is a cloud-based design platform that utilizes its state-of-the-art servers to process all the necessary algorithms. With Visme, you can work on all of your projects on any device that has a web browser and pick up where you last left off.

Another incredible feature of Visme’s that sets it apart from others is its Google Analytics integration.

In order to be time-efficient and make your design process go as smoothly as possible, Visme gives you the option to directly import your data from Google Analytics, Microsoft Excel, Google Sheets and Survey Monkey.

This makes visualizing your data a breeze. Instead of manually entering the values of your data, you can embed the link to your data spreadsheet in your presentation.

It will then automatically update your pie chart, graph, chart, heat map or whatever other visual data representation element you’re using to match your data exactly.

How amazing is that?

The internet has connected us all together. We now have the ability to share information at the speed of light with people all around the globe.

The best way to improve in designing data visuals is by receiving constructive criticism from those who review your work.

Sharing your data visualization presentations online with your colleagues should be an easy and effortless process.

Cloud-based applications make sharing and presenting my data visuals a breeze. By using Visme, you and your team will be able to collaborate and share your work seamlessly with one another.

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Having the ability to place comments on areas that need to be changed can greatly improve your team’s productivity, increase comradery and ensure that the end product is the best it can possibly be.

Presenting your data has never been easier.

Because Visme lets you start your presentation from nearly any device, you no longer have to worry about which operating system your venue is running. You can now launch your professional presentations from virtually any device, anywhere in the world!

You can also share an online link with your team members, controlling who can see your presentation.

Another option is to download it as a JPG, PNG, or PDF or post it directly online for all to see via an embedding link. The choice is yours on how you choose to share your data.

Data Visualization FAQs

Q. What Is Data Visualization?

Data visualization is the graphical representation of simple or complex data so that it’s easier to understand, analyze or present to others. It can be an intuitive way to represent trends, patterns and insight.

Q. What Is a Data Visualization Technique?

A data visualization technique is a method used to represent data visually, using charts, graphs, and maps. You’ll need to use various techniques based on your data and visualization goals or use case.

Q. What Are the 4 Stages of Data Visualization?

The four stages of data visualization are data collection, data processing, data analysis, and data presentation. First, you need to collect the data you want to visualize. Next, process the relevant information. Then, analyze the data for trends or highlights. Finally, select appropriate charts and graphs for visual representation.

Q. Which Tool Is Best for Data Visualization?

There are many tools to choose from, but Visme stands out as the best data visualization tool. It offers more than just data visualization; it's an end-to-end content creation tool. Visme provides intuitive graphs, charts, templates for documents, presentations or reports to present your data effortlessly. Each chart or template is customizable to meet all your data visualization needs.

Q. What Are the 3 C’s of Big Data Visualization?

The 3 C's of big data visualization are Clarity, Conciseness, and Context. You’re data visualization should always provide the following:

• Clarity ensures that your data is easy to read and understand, allowing the reader to effectively comprehend the presentation with or without accompanying words.
• Conciseness involves presenting only relevant information to prevent overwhelming or confusing the reader. Any data used should directly address the research question or topic at hand.
• Context provides additional background information or details to help the reader understand the purpose or interpret the visualized data accurately. This may include timeframes, sources, demographics, or events.

Create Stunning Data Visualizations With Visme

Whether you work in data science or you're just a person who likes to explain everything with bubble charts, it's important to communicate clearly and concisely with those around you.

We hope these 12 data visualization techniques will help you communicate clearly and effectively with those you come in contact with.

If you want to use these data visualization strategies, you can sign up for a free account with Visme today and start creating all kinds of charts, graphs, infographics and presentations.

If you still do not feel confident enough to create your own presentations, check out Visme’s free certification courseon crafting professional presentations.