5 Tips for Better Data Presentation

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Many of today’s visualization tools, including the two we sell—BIOVue and Tableau, give even the most non-technical user the power to create sophisticated graphics with just a few clicks.  This can be a double-edged sword.  Users who are not knowledgeable about graphic principles may be lured by the ability to put everything but the kitchen sink into a single graphic, making a dazzling piece of art that is difficult to decipher.  However, a visualization that is confusing or provides little information is not a good visualization, no matter how dazzling it is.  The goal of graphic analysis is to create a visualization that tells a story, not to create “data art.”

There is a lot of material available about data presentation—you can take courses in visual perception and graphic design; you can study mathematics, probability, and geometry; you can read about dashboards and analytics; you can devote years to studying the advancement of visual communication.  But if you have just a few minutes, you can read this article to get some of the basics.

Better Data Presentation

  1. KISS.  Remember the old KISS method?  Keep it simple, Sam.  You want your readers to be able to look at the picture and get the point right away.  Skip the 3D graphics and drop shadowing and other distracting graphic elements.  Choose fonts for your legend, labels, and axis markings that are easy to read and make them large enough to see without effort.  That might mean marking every other bar in the bar chart or writing outside of the wedges in your pie chart.  Avoid subtle color variations so readers won’t have to guess which shade matches which block in your legend.
  2. Choose the appropriate format to display your data. Use bar charts to show discrete data or data ranges, pie charts to show parts of a whole, or tree maps to show data in more than two dimensions like sales by product by region compared to budget.  Don’t create horizon graphs or multivariate heatmaps  just because you can.  Use accepted practices, for instance, create your graphics to be read from left to right and top to bottom.    Use the fewest number of variables that you can and still make your point.  Be sure that every color you introduce has meaning and is used consistently.  Use subdued or monochromatic colors except to highlight important data.  Leave the Jackson Pollack riot of bold colors for the art gallery.
  3. Make sure the data is relevant. Know your key target audiences and what information they need to make decisions.  Cut back on the actual data you show.  Don’t show a year’s worth of weekly data if one quarter’s worth of monthly data will tell the story.  When it makes sense, show summary data and allow the user to drill down to the detail.  Don’t add extra variables just because the data is available—make sure the data is relevant to the point you are making.
  4. Use space wisely. Users don’t like to scroll to find data and there is an extremely limited amount of immediately visible screen real estate.  Every graphic you put on a dashboard or report is there at the expense of other data, so be thoughtful in your selection.  Some visualizations such as gauges take up a lot of space and yield little useful information—think twice before adding novelty graphics.  But don’t overcompensate and cram so much data onto the screen that it is difficult to read or make sense of.  If possible, make the graphics interactive—instead of putting everything you can think of that someone may want to see on a single screen, give the user the ability to change the data with a click.  For example, instead of showing all of the sales regions side-by-side, present one graph and let the user click on which region he or she wants to look at.
  5. Make your visualizations appealing to the eye. While this might seem trivial, an aesthetically pleasing graphic or report will attract more attention and will generally be better understood.  And after all, that is the goal of your data presentation, isn’t it?

Have a little more time?  Here are a couple of books I highly recommend:

Few, Stephen, Information Dashboard Design:  The Effective Visual Communication of Data, 2006

Rasmussen, Nils, Business Dashboards:  A Visual Catalog for Design and Deployment, 2009

Tufte, Edward R., Envisioning Information, 1997

BIO Analytics Corp. sells two exceptional viewers that leverage the power of BIO business intelligence:  BIOVue and Tableau.  BIOVue is a workhorse—a versatile and affordable viewer perfectly suited for the frequent user.  From non-technical users to analysts, BIOVue provides all of the functionality most users need and allows you to create sophisticated graphics for reporting, ad hoc analysis, and dashboards.  Tableau provides advanced presentation graphics and dashboards with an easy-to-use interface.

Take a look at BIO business intelligence for your reporting and analysis needs. You can see both BIOVue and Tableau in action in our next webinar.

By Sandi Richards Forman of BIO Analytics, Corp., Microsoft Dynamics Business Intelligence (BI) Solution Provider

View demos of our business intelligence software and services for Microsoft Dynamics and feel free to contact me at sandi@bio4analytic.comwith any questions you may have about BIO or about business intelligence for Microsoft Dynamics.

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