We all get by with a little help from our friends. Let us share a tech tip with you and offer you an opportunity to learn more from the Red Pill Analytics team.
You spend all of this time and effort putting together an analysis to share with your users. But wait! Are your users able to quickly interpret the results in the way you are showing it to them? Data visualization matters and a few quick changes will improve the effectiveness of your visualizations ten-fold!
I like to follow Wasatch Snow Forecast because they are great at predicting when I might be unable to work due to “snow fever.” However, when they show charts like this one below, it makes me cringe.
Let’s talk through some ways to improve this chart.
- 3-D should not be used for data visualizations. Did Brian Head Resort have 80 inches of snow or maybe closer to 85? It’s too confusing with the 3-D bars to determine.
- The context of this tweet was talking about the killer amount of snow we’ve gotten this January. Would you have guessed that when looking at this chart? I would have guessed that they were showing how the snow gods love Brighton Resort this year. However, if I were trying to show that all of the Utah resorts were having a great snow year, I should show some context to compare to previous years to make it apparent that it’s a great year to ski utah’s greatest snow on Earth.
- The horizontal lines are distracting in this chart. A goal in effective data visualization should be to emphasize your data pixels and de-emphasize the non-data pixels. This means that the bars should be the main focus and anything distracting from showing that main goal that you are trying to get your users to see should be removed or decreased in emphasis.
Granted, when you are using Excel this chart might be as good as it gets. Perhaps I should head over to Wasatch Snow Forecast and enlighten them on using Oracle Data Visualization Desktop to create great looking charts! Maybe they should be watching Kevin McGinley’s vlog, #DataVizDaily.