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Art and Science of Data Visualization (Part 2)

Just a little more theory and background on Data Visualization, to eat up the rest of your weekend. Unlike the McCandless video, this video will take some time investment – but well worth it, if you want to charge your batteries on this topic.

(via Flowing Data) From earlier this year, Martin Wattenberg gives a talk on data and visualization. Some interesting points:

  • Data visualizations work well with large data sets
  • Interesting insight comes from borrowing ideas from different knowledge areas
  • Visualizations and analysis can help text “data sets” just as much as numerical data sets

Plus, a really interesting injection of artistic sense and sensibility into the “science” of data analysis – breaking WIRED magazine covers into component colors wheels, and seeing editorial patterns following patterns. Wattenberg’s summation on this particular visualization technique:

… an interesting phenomenon – the idea that you can visualize color.

I know what he means, it just sounds like he’s struggling for words to express a concept that is simple to understand visually; sort of a mini-proof of the “picture tells a thousand words” idea that is the fundamental reason why well-done data visualizations are amazingly effective.

Presentation fans, take note: Wattenberg also provides multiple examples of effectively reinforcing a discussion point by doing really interesting visualizations with openly available tools on the internet. Makes me question my “firmly held belief” that presenting live software to a large group is a a recipe for disaster. This is one of my personal takeaways from the video – live interaction helps the audience better understand the insights that they can get when working with the data. A least it’s better than a room full of bobbleheads when the “drilldown” buzzword pops up.

By the way – the MITWorld site has a huge collection of deep-dive videos; more on data visualization and empirical analysis, of course, but on a wider range of topics as well.

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