Stephen Few on Data Visualization: 8 Core Principles

stephen-fewDay 2 of Tableau's Customer Conference kicked off with a fantastic talk on data visualization by Stephen Few: "Perceptual Zen: Learning to Meaningfully See". Riffing off Garr Reynold's Zen theme from Garr's upcoming Presentation Zen talk, Stephen presented his 8 core ideals for effective data visualization tools.

Stephen says that data visualization is just a tool. We could build houses before we had hammers and saws, the tools just let us do it better. That is, assuming we've developed the skills to use the tool effectively.

Good data visualization takes the burden of effort off brain and puts it on the eyes. Stephen Few's 8 Core Principles that let us accomplish that are:

Simplify - Just like an artist can capture the essence of an emotion with just a few lines, good data visualization captures the essence of data - without oversimplifying.

We don't want a tool that gives us 19 more options after we decide we want a cloumn graph. We want a tool like Tableau that knows which visualization is appropriate and then creates it. Simple.

Compare - We need to be able to compare our data visualizations side by side. We can't hold the details of our data visualizations in our memory - shift the burden of effort to our eyes.

Attend - The tool needs to make it easy for us to attend to the data that's really important. Our brains are easily encouraged to pay attention to the relevant or irrelevant details. Stephen demonstrated this convincingly with a video similar to Daniel Simon's classic gorilla and ball passing.

Explore - Data visualization tools should let us just look. Not just to answer a specific question, but to explore data and discover things. Directed and exploratory analysis are equally valid, but we need to be sure that out visualization tool makes both possible.

View Diversely - Different views of the same data provide different insights. It helps to be able to look at the same data from different perspectives at the same time and see how they fit together.

Ask why - More than knowing "what's happening", we need to know "why it's happening". This is where actionable results come from.

Be skeptical - We too rarely question the answers we get from our data because traditional tools have made data analysis so hard. We accept the first answer we get simply because exploring any further is tool hard. More powerful tools like Tableau give you the luxury to ask more questions, as fast as we can think of them.

Respond - Simply answering questions for yourself has limited benefit. It's the ability to share our data that leads to global enlightenment.

"The best software for data analysis is the software you forget you're using. It's such a natural extension of your thinking process that you can use it without thinking about the mechanics." - Stephen Few

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