From the course: Data Visualization: A Lesson and Listen Series

Lesson: It's all in the details

From the course: Data Visualization: A Lesson and Listen Series

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Lesson: It's all in the details

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(mellow music) - So you're designing a data visualization. That's great. But you're going to have to make a bunch of really big decisions. What data analysis methodology will you use? What chart are you going to use? How are you going to pick the scale? But just as important as the big decisions are the tiny little details that can really make a difference in the quality of your work. So how do you make those tiny decisions? It's a lot to think about. What if I told you that there's a really simple process you can follow? It's something I've developed over the years, and it has a terrible acronym to help you remember. Yeah, it's WART, W-A-R-T. You see when we're working on a visualization and trying to finesse it to make it really sing, you can think of it like a beautiful thing that has just a few small words that need taken care of. Technically the acronym really should be W-A-R squared-T cubed, if you want to nitpick and be kind of nerdy about it. But let's imagine you started your project by cleaning the data and doing the analysis, and then you figured out exactly what it is you want your audience to take away from your visualization. After that, you created your chart. So far, you've probably invested quite a bit of time, and now is the time for the first two letters of the acronym, W-A, which stands for walk away. When you've been working for a long time on something and you're invested in it, it's very hard to change it and really difficult to even see what might need changing because you're so used to what you've been looking at and thinking about for so long. So first, just walk away and do something else. Now, once you walk away, you need to rest and then refocus. That's why it's R squared and not just R. Rest really means rest. You need to actually take some time for your brain. to let go of the ideas you've invested in and even let your eyes recover from seeing the visual patterns you've been developing. If you can, close your eyes for a few minutes or literally sleep on it and return to your task the next day. Once you've rested, you need to refocus. If you've seen me teach before, you may know about another set of acronyms I created, the KWYs. Now, don't worry about what the KWYs stand for. You can look them up in my other courses. For our purposes here, you just need to know that they're all about focusing on what you have to say about your data, what is the data saying, and what does your audience need to hear? I'm suggesting you need to get out of your own head and come back to the KWYs. What are your goals? What are you really trying to say and trigger in your audience? Just test your real KWYs against what you've created and maybe you'll immediately see small changes you can make to improve it. Finally, you need to tweak three things. Yeah, that's a totally arbitrary number. But I guarantee you if You look for three things to improve, you'll find them, okay? So look for three things, changes to things like labeling, colors, scales, context setting text, use of shape or contrast. I bet you can easily find three ways to make your visual better. So take the time, follow this process, and tweak the little details until time runs out, or your work is perfect or close to it. Up next, we'll hear from Andy Kirk, who has a series of blog posts he calls "The Little of Visualization Design," and it's all about the small decisions that make a big difference in this craft.

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