Big Data Visualizations: A Good Use of the Chord

25 Nov

There are a number of visualizations that I’ve included in my BI solutions over the years that were typically reserved for data mining applications when visualizing data clustering such as this “blog galaxy” example from datamining.typepad.com:

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Data mining is a practice that has been around for decades and has a goal that is very similar to what we attempt to achieve with business intelligence and Big Data Analytics: uncover meaning, knowledge and value from data. The biggest differentiator, in my mind, that adds value from applying data mining algorithms to visualizing and demonstrating business value, which can be used to make better business decisions, is the intersection of data mining / analytics and business intelligence.

In today’s world, algorithms used for mining and analytics are being applied to Big Data sets, which implies a different approach to data management and processing. But it also means that ideas such as data exploration & data discovery are beginning to permeate modern every-day BI solutions.

I just want to focus on one common visualization that you will see a lot in Big Data Analytics: Chord graphs. Below is an example from Pentaho where you can see that a chord does a good job of demonstrating connections, paths, and relationships between attributes and dimensions.

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That comes from bigdatagov.org. We also use Chords often for our “data scientists” in Web analytics who are looking for paths to maximize conversions.

Taking the chord idea to the next extreme comes from a project by Colin Owens at http://www.owensdesign.co.uk/hitch.html where he is exploring different pros & cons of visualizations that demonstrate relationships. Here you can see some of the chord’s shortcomings in terms of showing influencers, a key aspect to marketing analytics:

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But here is a great example of where the chord shines by using a data set that makes sense to most of us, not just statisticians:

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Click here to interact with that chord graph. This should give you a good idea of the utility of a chord graph. In this case, Chris Walker used 2012 U.S. census data to show Americans moving between states in the U.S. When you hover and select areas of the radial chord, you can easily see paths (very important in Web analytics and marketing) with size of links related to # of migrations.

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