Visualizing data helps others make sense of it. And if your success depends on getting others to see your data in a certain way, rather than getting lost in its complexities, then data visualization can also be a powerful psychological ally. Even the simple act of using the right number(s), shade(s), and hues of color when presenting your data could help you get the exact results you want from your next lesson or presentation.
So, what are the best and most effective practices to consider during data visualization? Let’s take a look at just a few of them.
Best Practices for Easily Bringing Your Data to Life Visually
Your goal is to reduce complex data points and present them in ways that are simple to understand at a glance. Here are 6 ways to do just that.
Less Is More
If we’re inundated with too much information, we can miss the entire point being made. Thus, the best advice is to Keep It Simple (KIS). This ensures that you don’t get carried away by overwhelming your audience with details that distract from your core message.
Show the Big Picture
What does it all add up to? Audiences, especially at higher echelons of management, prefer a big picture view as opposed to getting mired in minor details, so make sure the data you’re presenting supports the big picture rather than feeling like disconnected talking points. For example, instead of providing rows and rows of complicated data and leaving your audience to wonder how it all connects, refine your data as much as you can into higher-level information that establishes your big picture (but be prepared to provide additional details if requested).
Choose Your Colors Carefully
Colors have powerful emotional and social associations (but these vary from culture to culture), so make sure your colors are painting the picture you intended for your specific audience — and if your audience is international, double-check those associations. You may also have individuals with special visual needs in your audience, so choose your colors and fonts accordingly.
Too Much Precision Can Sometimes Be Distracting
Data visualization is all about helping your audience visualize trends and patterns, not about getting down into the weeds, so consider what level of precision is necessary to convey your big picture point. For example, does your audience need to see sales data in the format of “$943.12 vs. $1107.93,” or is the format of “$940 vs. $1100” sufficient and more impactful in supporting your point? Do they need to know that “31,143 individuals were affected,” or simply “over 30,000”?
Again, your goal is not to obfuscate the truth or mislead your audience, just to convey your core points most clearly. Thus, making granular details available in supplementary information (like an appendix) may be necessary for the sake of veracity, even if your primary presentation relies on averages and estimates for the sake of simplicity.
Use the Right Visual Aids for the Situation
Consider a problem: you have to convey a relationship between death rates and cause of death. Which charts or graphs would you select for this job?
While displaying your data in two pie charts might be adequate, a bar chart may be more impactful. That’s because a bar chart will not only rank cause of death (highest to lowest, or lowest to highest), but you can also use bar length to visually compare each cause against others on the chart, and linking those two data sets is a critical need in this case.
For a comprehensive guide to selecting the right chart for the right situation, bookmark this reference from Hubspot.
Your Tools Matter
While using tools like Excel or PowerPoint can help in your visualization efforts, there are plenty of services and apps to help you convert your data into more accessible and attractive images, but each has its own strengths and flaws. You may want to evaluate options like Qlik, Tableau, and PowerBI, as well as the services suggested by The Tech Edvocate, and then select the right tool(s) for your needs.
“Does This Make Sense?”
Since simplicity and clarity are your goals in data visualization, you need to know if all your efforts are actually producing the results you’re aiming for.
Before you make a presentation or launch a course, show your visualizations to someone who has no familiarity with the subject and ask them what the data means. If they can come to your desired conclusion based solely on the visualizations you’re presenting, then your target audience should also be able to do so. But if not, you may need to go back to the drawing board and refine your approach.
Measuring Data Visualization Success
Mastering data visualization tools is just part of your path to effectively using data. At the end of the day, your efforts to help your audience understand the data being presented will result in success only if they find your presentations clear and actionable. Better decision-making, faster response times due to less complex data streams, and higher trust in data and its validity – these are all ways to measure the success of your data visualization efforts.
(And if your audience still isn’t coming to the conclusion you want them to no matter how you present your data, maybe the issue isn’t your data at all but your audience’s preconceptions. But that’s another topic for another time.)
Image: “I Heart Graphs” by Ken Kuchih via Flickr Creative Commons License