Posted by Jon Pilkington on May 19, 2015

You could have the most sophisticated data analytics engine at your disposal, but it means next to nothing if you can't make sense of the finished intelligence.

Essentially, organizations need visualizations that present intelligence in a way that complements the collected data. Bottom line: The point of using visual analytics is to understand information in the best manner possible. Listed below are two examples of visualizations that fit this criteria. 

1. The eloquence of rappers 
Stereo Gum acknowledged a visualization created by data scientist Matt Daniels, whose objective was to deduce how extensive each rapper's vocabulary was. First, he started by taking 35,000 words from each artist's discography. Then, Daniels pulled unique words from each rapper's data set, ranking their literacy based on how many he found. 

The visualization shows cartoon drawings of popular hip hop artists in different colors, which represent where particular artists are from (East Coast, West Coast, etc.). Along the X-axis is a chart that ranges from 3,000 to 7,392 unique words. Each rapper is given a bubble showing the number of unique words they used throughout their careers.

To give observers a better idea of how eloquent the surveyed rappers were, Daniels inserted a small dot representing unique words aggregated from Shakespeare's Plays (which didn't come out on top, in case you were wondering). 

Why did I choose Daniel's visualization? Because it presents finished intelligence in a clear manner and provides additional data (i.e. where the artists are from) to provide extra context.

2. The No. 1 cause of data breaches 
One particular visualization that caught my eye was one describing the sources and severity of data breaches. Information is Beautiful's representation supplies viewers with interactive, color-coded bubbles that draw conclusions based on the following factors:

  • Whether breaches were caused by accidents, hacks, inside jobs, lost or stolen devices/media or poor security
  • How many records were stolen in each instance
  • A timeline of notable security transgressions from 2004 to 2014
  • Which sector a data breach victim participates in (government, military, energy, retail, etc.)

One can notice that the frequency of successful hacking attempts has risen over the past two years. The largest data breach caused by lost or stolen devices resulted in 26.5 million records owned by the U.S. Department of Veteran Affairs being exposed. The most detrimental inside job occurred at Court Ventures, which lost 200 million records. 

Overall, these two visualizations are excellent examples of intelligence presented in an optimal manner, and enterprises should take note of their designs. 

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