As I try to understand energy consumption patterns on a daily basis by analyzing Big Data, I continue to see that in many other fields these are proving extremely useful. Take for example the analyses based on college dropping drivers made by Georgia State University.

By a careful analysis of the over 140.000 students records, 2.5 Millions grades, and other data the university managed to identify 800 different behaviors correlated with dropping out. By taking adequate counter measures, the University managed to reach a gradation rate of 54% in 2017 while it was only 32% just a decade ago.

How did they achieve this? Take a look at the very insightful article by Bill Gates on his blog and to the related analysis by the Post.