Data visualization for analysis and understanding complex problems

Enrico Bertini, a professor at New York University, delves into the less flashy but equally important branch of visualization: analysis. Much of what Enrico describes applies to the other branches too, so it’s worth the full read:

One aspect of data visualization I have been discovering over the years is that when we talk about data visualization we often think that the choice of which graphical representation to use is the most important one to make. However, deciding what to visualize is often equally, if not more, important, than deciding how to visualize it. Take this simple example. Sometime a graph provides better answers to a question when the information is expressed in terms of percentages than absolute values. I think it would be extremely helpful if we could better understand and characterize the role data transformation plays in visualization. My impression is that we tend to overemphasize graphical perception when content is what really makes a difference in many cases.

Getting to that what often requires iteration between the analysis and presentation facets of visualization. I spend about the same time on the analysis side as on presentation, and that’s only because I’m more fluent with my analysis tools. I don’t have to spend a lot of time reading documentation. The amount of production during the analysis phase is definitely much higher.