The Top 12 Tips for Data Visualization

by   |   March 20, 2017 5:30 am   |   1 Comments

Bernard Marr

Bernard Marr

The best data in the world isn’t worth a hill of beans if no one can understand it.

A data analyst’s job is not just to collect and analyze data; he or she must then present it to the interested parties and end users who will act on that data. That’s where data visualization comes in.

Most data analysts are not necessarily graphic designers or experts in data communication, and so a lot can be lost in translation from the data- “-gathering”? to the boardroom. I find myself increasingly teaching data visualization courses to data-science teams who have identified that as an area of weakness.

If your job is to present findings from a set of data or analysis to a group of laypeople, then it is also your job to present it in such a way that they can easily understand it and take appropriate action.

Here are some key tips to help turn data into insights people will understand.

  1. Keep the audience and their information needs in mind.
    It is vital to customize any data visualization to meet the audience and their information needs. Think of who is in that audience and then think about the questions they would like answered.
  2. Choose the right chart.
    Not all charts are created equal. Some do a better job than others at displaying different kinds of information. This excellent flowchart can help you choose the best chart type to display your information.
  3. Go beyond PowerPoint templates.
    The most popular visualization tool by far is PowerPoint, but its built-in templates may not be doing your data any favors. Instead of trying to get fancy (we’re looking at you, 3D pie charts), keep your visualizations simple and uncluttered to be as clear as possible.
  4. Form follows function.
    In other words, consider how your audience will use the data and let that inform how you present it. Think of your presentation as a dashboard in a cockpit, and present only the most relevant, useful information in the clearest way possible.
  5. Direct people to the most important information.
    When designing your visualizations, use sensory details like color, size, fonts, and graphics to direct attention to the most important pieces of information.
  6. Use graphs and tables appropriately.
    Graphs should be used to display information about data relationships, patterns or how things change over time. Tables should be used when you need to show precise values. From my experience, you should reduce the use of tables and increase the use of graphs.
  7. Provide context.
    A good visualization will prompt the user to act on the data being presented, but that’s hard to do if you haven’t provided any context for that action. Use color, size and other visual cues to provide context and include short narratives that highlight the key insights.
  8. Align displays—and data—correctly.
    Make sure that your displays of information are horizontally and vertically aligned so that they can be accurately compared (and don’t create any misleading optical illusions).
  9. Use color wisely.
    Color should be used to draw attention to key pieces of data, not just to brighten up a dull dashboard or presentation. In addition, choose your color combinations carefully. For example, try not to use red and green in the same diagram, as they both appear brown to people with color blindness.
  10. Titles provide information.
    Give charts and graphs useful, explanatory titles that help explain the focus of that particular visualization. View the title as your “headline” and use it to draw people in, focus them on the right questions, or give them a snapshot of the key insights.
  11. Axis labels and numbers should be clear.
    Avoid fancy labels and gauges that can get in the way of clarity. Label the axis of a graph or chart clearly and start at zero—unless you have a strong reason not to—e.g. when all the data is clustered at much higher values.
  12. Provide interactivity when appropriate.
    New generations of data-visualization tools make it possible to build interactivity into many visualizations that can benefit the end user. But again, remember that this isn’t a parlor trick, and should be used when interactivity can clarify, rather than confuse, the presentation of data.

By following these basic principles, you will increase the effectiveness of your communications and presentations, allowing key stakeholders to make better, more informed decisions about the data you’ve collected and presented.


Bernard Marr is an internationally best-selling business author, keynote speaker and strategic advisor to companies and governments. He is one of the world’s most highly respected voices anywhere when it comes to data in business and has been recognized by LinkedIn as one of the world’s top 5 business influencers. In addition, he is a member of the Data Informed Board of AdvisersYou can join Bernard’s network simply by clicking here or follow him on Twitter @bernardmarr


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One Comment

  1. Posted October 13, 2017 at 3:22 pm | Permalink

    I like these points! Especially your point about making a viz interactive when appropriate. (It isn’t always called for!) The ability to modulate the data—the element of interactivity—enables end users to test hypotheses and assumptions. A single, modifiable view can deliver instant insights that might take hours to discover through traditional database queries, static reporting, or dashboards. By transforming complex data into interactive pictures, we help everyday users ask and answer the difficult business questions they face every day.

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