5 best practices for data visualization

18.06.2021 by Līva Luriņa

What is data visualization?

Data visualization is the art of transforming quantitative data into graphics, such as charts, graphs, tables, or infographics.

The goal of data visualization is to provide recipients with a comprehensive yet easy-to-understand reflection of information, whether it’s a small set of essential metrics or an enormous amount of big data that needs to be visualized.

Why is data visualization important?

Nowadays, the amount of information created and consumed every second is tremendous. In 2020, we all ended up with 64.2 zettabytes of data and information created, captured, copied, and consumed worldwide. Compared to 2019, the number has increased by 56.6% because of the global pandemic and changes in people’s habits. In upcoming years, the volume of data is going to expand exponentially, as Statista forecasts. This is huge!

That is why the credibility, visibility, and comprehension of the information are so important. If done right, data visualization can become an important asset to reach goals and engage audiences for businesses, educators, marketers, sales and project teams, and everyone else who works with loads of data.

On the other hand, publishing bad charts and graphs can lead to detrimental results.

 

Data visualization best practices

In this article you’ll learn 5 best practices on how to create impactful data visualizations. So, let’s dive in.

1. Set a goal and clear message

Data visualization plays a vital part in communication, so you have to set an achievable goal and a clear message.

Whether it’s a performance overview, behavior analysis, process efficiency review, or a call to action, the message of your story must be clear.

When you’ve clarified the main message, it’s time to identify for whom it’s addressed. Choose your target audience to create charts that are compatible with their knowledge and expectations. It should be easy to process data and understand the message as quickly as possible.

set_a_goal_and_clear_messageFor example, the depth and approach to how an organization’s management communicates the data for stakeholders or employees will be much different than educators explaining concepts for students or marketers building awareness on social media.

Setting the goal and choosing the target audience are important elements for a good data visualization, not just because you’ll have a clear vision of the outcome, but also because you can choose the correct chart for your data.

2. Choose the right chart type for your data visualization

One size does not fit all, and that’s true for data as well.

Once you’ve set the goal of your dataviz project, it’s time to put the numbers into a graph to emphasize the message. There are 4 main types of charts, based on what you’d like to express.

choose_the_right_chart_type_for_your_data_visualizationComparison

Comparison charts are the right choice if you want to compare variables from one or many categories (e.g., sales by department). They are also used to measure items and highlight trends over time, such as the average temperature in Tokyo for the past 3 years.

The most used comparison charts:

Relationships

To reveal the connection or correlation between two and more variables, the relationship chart is the perfect match. For example, to show the relationship between fertility rate and life expectancy in different nations, the best fit would be one of the following:

Composition

Composition charts express the structure of a total and change over time (e.g., distribution of your monthly expenses). The most common composition charts are:

Distribution

To show how items are distributed over time and to identify the trends, distribution charts are very useful. Common distribution charts include:

To better understand each chart type in detail, watch our video about how to choose the right chart for your data.

3. Ensure context and comprehension of data

Keep in mind that every data visualization project should provide value for the audience. Dataviz is not about numbers that are put into colorful bar charts – it’s a set of visually displayed information that should be comprehensive yet easy to understand.

ensure_context_and_comprehension_of_data

To provide full context of the displayed data, follow these tips:

  • Include only necessary data – if it doesn’t support the story, leave it out
  • Create a strong title that builds up the message you’ve set in the first step
  • Scale the chart appropriately with equal intervals on each axis
  • Make sure the labels and legend are easy to read and understand
  • Organize the data logically to ensure they’re easy to compare at a glance
  • Tell the whole story instead of only showing the most impressive numbers
  • Add the source of data to build credibility and trust, and to provide an opportunity to learn more

4. Design and polish graphs and charts

There’s a thin line between good visualization and not-so-good. While the content should be visually appealing, you should avoid having too many colors, fonts, layouts, and accents. Keep it simple.

design_and_polish_graphs_and_chartsLearn these crucial data visualization tips:

  • Choose a font for the title, axis labels, and legend that is easy to read. This is important to make sure the viewers get the message clearly.
  • Try to avoid mixed or rainbow color palettes – they tend to be ineffective. Instead, choose one tone for the chart or add another if there’s a need to highlight data. Bright colors attract eyes more quickly, so use them to attract attention to a specific part of the graph.
  • Add data labels directly to the lines or bars, especially if it makes the chart easier to read at a glance.
  • Don’t overuse grid lines. Use them only if they actually facilitate the readability of the graph.
  • If presenting data on behalf of the organization, always try to use the company’s branding: colors, fonts, and styling. This will help your charts and graphs look more professional.
  • Test it. While you’re already familiar with your data, show the design to a friend or colleague – can they get the whole picture in less than 30 seconds? If so, you did a great job!

5. Choose the right data visualization tool

Data visualization should be done precisely but not in a time-consuming way. Choosing an intuitive tool for the job is incredibly important, especially if you’re not a graphic designer but still want to wow your audience.

choose_the_right_data_visualization_toolInfogram helps you create engaging infographics and reports in minutes, ensuring the best design approach to display any kind of data.

Simply select the most appropriate templates for reports, charts, maps, or social media posts, adjust or customize the content, then save your interactive project in a wide range of formats.

Even if you’re building charts on your own, doing some research on the best data visualization examples might be useful to get fresh ideas or inspiration for further projects.

 

 

We believe that among the different types of communication, data visualization – if done right – is one of the most effective ways to build awareness and credibility, provide value, and answer strategic questions.

For more insights and practical examples about chart design best practices, check out our article, “Do This, Not That: Data Visualization Before and After Examples”. Keep these practices in mind while starting a new dataviz project and you’ll amaze your audience with your engaging charts.

Do you feel inspired to turn these learnings into practice? Get started with Infogram for free and easily turn your data into comprehensive and stunning designs.