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Noah Iliinsky: Tech Talk on Designing Data Visualizations

April 18th, 2012 · No Comments · General


Note: This post was written by Yael Garten, a Senior Data Scientist at LinkedIn. Yael joined Linkedin in 2011, where she leads our mobile analytics team. She previously worked at Stanford on text mining, personalized medicine, and biomedical informatics.

We live in an era of Big Data. But how do we use all of that data to answer questions and communicate those answers effectively?

My colleagues and I at LinkedIn were fortunate enough to hear answers from Noah Iliinsky, who literally wrote the book on designing data visualization.

Earlier this month, we hosted Noah at LinkedIn to give a tech talk on “Designing Effective Data Visualizations“. We are proud to make these tech talks open to the public, and enjoyed a great mix of attendees from local companies and universities. If you couldn’t attend the talk in person or remotely, I encourage you to watch the recording, embedded above.

Why do we visualize data? As Noah tells us, visualization makes data accessible. It gives us faster access to actionable insights and allows access to huge amounts of data. Visualization enables both data exploration (when you are still trying to discover the story) and data explanation (when you have a story to tell). Noah reviewed some great examples (watch the talk!), with an emphasis on the dos and don’ts of data visualization.

In particular, he provided a step-by-step framework for traversing the path from question to answer:

Phase 1: Decide what to visualize.

  • Understand the question your audience wants to answer.
  • Understand the actions they are hoping the answer will drive.
  • Consider who is consuming this data — their needs, biases, etc.
  • Decide what data to use — and what data not to use — and what relationships you are interested in.
  • Explore the data and construct a storyline.

Phase 2: Decide how to visualize it.

  • Use appropriate visual encodings for data and relationships (cf. http://complexdiagrams.com/properties).
  • Limit the data you include.
  • Use position for your most important relationship.
  • Try different axes.
  • Show your visualization to different people, without explanations. Show an expert, show a layman.
  • Iterate, iterate, iterate!

Noah also shared his thoughts on how to visualize social networks. He recommended useful tools for data visualization, including Tableau, Spotfire, D3, Processing, ggplot2, Omnigraffle, and OmnigraphSketcher.

Finally, he left us with key lessons to take home:
  • You are not your audience. This is a huge lesson that all of us must internalize to be great at what we do. Consider what you need to communicate to marketers, investors, member of the general public, etc.
  • Do user research! Understand your users’ hopes, dreams, and favorite flavors! Understand their identity, their jargon, culture, etc.
  • Remember that your success is defined by your customer’s success. If you can’t satisfy your customer’s needs, you have failed — no matter how insightful your analysis.

You can enjoy the talk by watching the embedded video above. And you can find more LinkedIn tech talks on our YouTube channel.

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