You know you need to get more visual with your data. That's been a big theme for 2013. But just because you're comfortable working with data doesn't mean you know beans about presenting it visually -- and that may have you scared.
The last thing you want happening is for business users to dismiss the insights you've worked so hard on because your heat map is a mess or your bar charts too confusing. That's just as bad as tossing a massive spreadsheet at them and saying, "Here, you find the pattern."
So yes, the thought of creating visualizations can be daunting for many data analysts. Panicking won't help; preparation will.
Taking the time to learn the right way to present data visually will keep your business users from seeing red over the work you produce. For advice on how to get started, we turned to Tricia Aanderud, president of BI consulting firm And Data Inc. and writer of the BI-Notes blog. Aanderud, who specializes in helping companies transform their data into meaningful visualizations, joined us earlier this week for an All Analytics Academy lecture on the "what, when, and why" of data visualizations. (You can view the lecture on demand).
Here are her four tips for getting started with data visualization.
Study with the experts. This discipline comes with its own set of gurus, folks who have been studying the art of presenting data visually long before "data visualization" became this year's buzz. These include, but are not limited to:
Read their books. Watch their YouTube videos. Check on the visualizations they have on their websites, Aanderud said.
Reproduce visualizations. Head to the web, find data visualizations that interest you in some way, and play around with recreating them. Here's one, for example, that Aanderud shared during her lecture. Can you spot what's wrong? How would you do it differently?
Experiment. Download some data (there's enough available from public sources) and play around with it. "There are free tools out there, but Excel works just fine" for this purpose, too, Aanderud told us. "Look at the data, ask questions, and figure out, 'OK, can I display it? How would I? Does a line chart work better? Does a pie chart work better in this instance?' "
Allow critiques of your work. And don't get bent out of shape. Remember, she said, "you're going to learn more if something fails than if it succeeds... and experience is what you get when you don't get what you want."
This all sounds like sound advice to me. Do you have any of your own beginner recommendations to share?
Visualization of info done properly can help show critical info better than any chart. Starting with good quality data and implamenting it onto a map, as you've done, makes it easier to see a problem and solution. While I saw some people commented on the color choices as an issue, I can still see the data and know that if given more room for this chart it would be easier to see difference in colors.
Jeff, when you say you make what you're doing clear in the presentation do you mean the oral presentation that comes along with delivering the visualization or in the visual presentation itself? I'm wondering, because while the former helps there is the problem that the visualization lives outside the presentation, no?
@CandidoNick, to me this came off as rather amateurish -- somebody playing around with heat map capability without really thinking about the data presented and readability (and who knows, maybe that was the point -- to play around with heat maps but not for "real" use). There are way too many categories, and therefore colors, to make this easily digestible, which makes it quite ineffective. Plus, as Tricia pointed out during the lecture, the salary ranges aren't equal in all categories. Another no-no.
I understand that heat maps are meant to get more vibrant as the concentration increases, so I assume differentiated colorings would defeat some of the purpose. However, greater contrast would be a welcome prospect.
How info appears may be the most critical part of presenting compelling data. These points are all fine, quality ideas that deserve consideration when preparing data for the big screen.
As for Aanderud's data map, the issue lies in the color choices. They are far too similar to one another, in my mind. And Alaska is very stretched out, hahaha.
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