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Bottom line on Data Visualization

Guest blog post by Michael Bryan

The market for data visualization software has bloomed. I'm suspicious.

Companies like Tableau, Spotfire, SAS Visual Analytics, Qlik and Zoomdata are positioning their tools far beyond traditional business intelligence.  Capabilities for graphically navigating data, recognizing patterns and finding relationships are growing in both functional and economic scope.  These new tools can provide charting forms only imagined in the last decade like word clouds, circular hierarchies, tree maps and stream graphs.  Check out the D3 (data driven documents) javascipt library for inspiration.  All this innovation begs a critical question:

Is data visualization

  • an entirely new dimension of data management
  • a subject within analytics, emerging with new tools
  • a rebranding of old subjects like business intelligence, dashboards and reporting
  • or something else?

On the one hand, visual is not new.  In 1983, Tuffle wrote "The Visual Display of Quantitative Information" which never stopped selling.  In 1987, Rockhart and De Long offered "Executive Support Systems" and launched the very user centric EIS age.  Comshare, IRI, Pilot and Arbor Software launched the 90's OLAP generation with its own concepts.  And, the last decade, we've seen familiar players in Business Intelligence leap frog each other, continually competing on presentation. Face it - "visual" sells software.

Analytic visuals aren't new either. Archimedes had charts. He just used a pen. The statistical suites all have rough but ready graph capabilities. Basic, and un-pretty, plots are among the first steps of exploratory data analysis. So, treating data visualization as innovative comes with a very high burden of proof.

I could buy the an argument that Big Data has a consequence of Big Graphics.  We are capturing more detail, we can store it and we need to study it.  So, data science has a ground to need advanced visuals.  But, I'm guessing that data visualization licenses outnumber data scientists by a hundred fold. 

Tufte's original book included a famous duck.   The picture illustrated, for Tufte, irrelevant and useless presentation.  So far, I haven't seen reasoning to treat data visualization as much more than a next generation duck.

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