Visualize to simplify, not to complicate
Data visualization is the practice of converting data into visuals for easy interpretation, in order to discover patterns and other valuable information. So basically it is done to simplify the process of understanding the data we possess.
But if not done in the correct way, it may lead to creation of visualizations so complex that they require you to break your head even to simply understand the kind of data which they are providing. Usually accompanied with a legend, these visualizations further complicate the process of understanding data, which I think defeats the purpose of visualization itself.
But how do we end up with something so complicated by following a process intended to provide us with simplified results?
Well that’s because data visualization itself has become a complicated process having a variety of strategies that can be adopted as well as a lot of different aspects which need to be incorporated.
If you ask someone what a successful visualization consists of, you’ll get to hear things like visual form, storytelling, strategic analysis and what not. And everyone’s got their own take on what a great visualization should consist of. So with all these techniques to follow and all these aspects to include, we often forget the actual purpose of visualizing data, that of making it easy to understand.
And an attempt to create something encompassing all these aspects is what leads to creation of those complicated visualizations which try to incorporate eye-candy visuals and engaging narratives. And somewhere in this process the focus on the data which needs to be put out there for the viewers is lost.
And though these aspects are important for creating good visualizations, they shouldn’t divert us from our main task, that is to represent data in an easy to understand manner. Because after all, the more easy it is to grasp the data from the visualization, the better we will be able to use it.
