Maximum “information throughput” can still guide legal managers when graphs display data

The legendary Prof. Edward Tufte gave a keynote presentation in September 2016 at Microsoft’s Machine Learning and Data Summit.  Tufte’s ambitious subject was “The Future of Data Analysis”.   You can listen to the 50-minute talk online.  Early on he emphasized that you display data to assist reasoning (analytic thinking) and to enable smart comparisons.

Tufte frequently referred to data visualization as a method aimed to maximize “information throughput”, yet also to be interpretable by the reader.  I took information throughput to be engineering jargon for “lots of data presented.”

Maximal information throughput, from the standpoint of legal managers, has almost no relevance.  The data sets that could be analyzed by AI or machine learning techniques or visualized by Excel, Tableau, R and other software are simply too small to justify that “Big Data” orientation and terminology.

That distinction understood, legal managers should take away from Tufte’s model and recommendation that when you create a graph, strive to present as much of the underlying information as you can as clearly as you can so that the reader of the graph can come to her own interpretations.

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