Data Visualization is UX
A lot of people consider themselves either analytics people or creative people. Left brain or right brain. But data scientists and data visualization uses both. Designing the experience of your data is critical to making your analysis memorable and usable.
There can be a barrier between the ‘hard numbers’ and how these are presented when you think this way though. If you want to get good at data, you have to get good at designing how you explain your data. I’ve seen it and done it many times - business data analysis that is too complicated, too overwhelming, or not actionable doesn’t live long. It gets presented, discussed, and then sits there - only to start the analysis process again. This goes beyond how you do your analysis, and encompasses how you present your analysis.
The design of your presentation, using any medium, is critical. If people don’t understand and take action, who’s fault is that? As a data scientist and analyst, it’s your job to make sure the data is useful. Storytelling with data is getting an increased focus recently, and there are so many great writers and speakers out there. And if storytelling doesn’t speak to you, think of your analysis as data user experience.
I started in the world of design and I have an architecture degree and my master’s from PennDesign at the University of Pennsylvania. Even with all of this, I still hesitated to call myself a designer for a long time. Other people were more innovative, more technically advanced, and I saw them create things that seemed like genius. As I went through my schooling, I realized that I also had a valuable perspective, and that design is a tool, not a trait. Use it to better convey your work for a better audience experience.
Ask who is your audience, what medium they're experiencing your analysis through, and what challenges you're solving. All of these should inform how you want the audience to experience your data.
Data visualization will be better served when users enjoy and relent the presentation. The field is going to keep advancing by using storytelling and UX, and these tactics are going to drive better informed data driven decisions.
Design shouldn't be scary.
Even though I know from my own experiences the high minded uses of ‘Design’ can be, breaking it down to smaller parts, allows you to approach design the same way you approach analysis.
Choosing the right metrics, slicing the data creatively are all designing data choices. The same care should be taken in how you explain this data. Colors, animations, spoken words, and all the other elements to a presentation are the same choices. They are tools, and should work together to make it a delight to experience your data. Good data design is focused on the user's experience.