How to improve a bad data visualization
Learn how to revise and resubmit your data story.
As part of the learning process of creating good visualizations, you will create bad ones.
It’s inevitable, especially when learning in a field that you may not be too familiar with.
But rather than simply abandoning bad visualizations, a much better option is to think about what went wrong and revise it: doing this allows you to learn how to improve quickly.
But it can be tricky to figure out how to do this: after all, if you were the one that created a bad visualization, how can you know where to start to fix it?
In this case, one of the best ways of doing this may be a UX technique you’re familiar with: Heuristic Evaluation.
The need for revision
One of the most common resources most recommended for practicing data visualization is #MakeoverMonday.
Every week, a new data set and visualization are posted, and users are asked to revise the visualization provided based on the data and make their own.
Doing so forces you to take a closer look at the visualization, and the message of the data set itself. In particular, are the metrics highlighted the right ones to present?
But one of the things you quickly learn when you do this often is that it’s not just about presenting data effectively: it’s about telling a story.
Figuring out what story the data tells helps improve not only the design of the visualization; it can help improve your audience’s understanding.
Here’s how to break down a data story.
Understanding Data Stories with Heuristic Evaluation
Creating stories about data is only human: it’s the ability to revise consistently that makes a story sound.
– COCO KRUMME
