A statistician and Yale University professor emeritus of political science, statistics, and computer science, Tufte is known as a supreme master of the art (and science) of delivering information visually. He's inspired many of today's data visualizers, among them Jonathan Schwabish, a US economist who says he considers Tufte the "godfather of modern data visualizations." For him, a one-day Tufte workshop turned into an eye-opening experience on how "we can use graphics and data visualization in a more strategic way and a way in which we can show our data in clearer and more innovative ways."
Since then, Schwabish has been putting what he's learned into his work, creating data visualizations in his role as a policy analyst. "I put those things into practice, and keep thinking about ways and better ways in which we can present our data," says Schwabish, who now runs his own workshops about visualizing and presenting data for people in public policy.
here on AllAnalytics.com. I've included four takeaways below. Watch the video for the full rundown!
- Know the differences between exploratory and explanatory data visualizations. Interactive data visualizations, those available through a web interface, for example, can be exploratory or explanatory in nature. Exploratory interactive visualizations encourage users to go into the data and play around with it, maybe even coming up with their own conclusions from it, Schwabish said. In explanatory visualizations, the data visualization "tells a story and the interactivity is leading you down that path."
Static visualizations are explanatory in purpose, too, since the user doesn't have the capability of working with the data or playing with the graphics. Static data visualizations include your basic bar charts and pie charts, as well as those towering infographics -- compilations of text, graphics, and images that have become so popular today. (View our own latest such data visualization, 3 Levels of Analytical Sophistication, and see one of Schwabish's below.)
- Devote time to plotting out the infographic. Don't give short shrift to the amount of time needed to think about how to present and tell the story of your data, said Schwabish, adding that he spends about 70 to 80 percent of his time laying out his story for the larger infographics he creates. "I'm in an analog world here, actually sketching with pen and paper and colored pencils." Then you can move into the graphics software.
- Understand what your audience wants. While you might gravitate toward wanting to create the fun and fancy type of data visualization, don't do it if it serves no purpose for your audience. For example, Schwabish mostly prepares static data visualizations because he's trying to provide members of Congress and their staffs the bottom-line, statistic, or headline piece of information. "At this point, I'm not sure my audience is really interested in an interactive infographic where they have to weave and explore and click -- that's not my audience." The standard static data visualization serves as much purpose as the interactive one for the right audience.
- Deliver insight. Regardless of type, data visualizations ought to give users fresh insight. "If you can give your users insight that they may not have gotten from some other means, be it the written report, some other website, or some other source, that, I think, is a successful visualization."
I would agree. How about you?
All Analytics will be continuing our ongoing series of video chats on data visualization next week, when business intelligence consultants Tricia Aanderud and Ben Zenick join us for a conversation on how to create great data visualizations. You'll find us on Facebook next Wednesday, June 5, at 2:00 p.m. ET. I hope you can tune in!