The best new techniques in data analysis get at the constant of causality, what causes what? That’s what you really want to know in data. And when you start to think about causality, causality is usually some human behavior that’s driving that. So the confluence of behavioral economics and behavioral sciences tells you this is how humans behave and taking that, together with the data, and trying to create these behavioral causal models is really the Holy Grail of data analysis.
Former Citigroup CEO Vikram Pandit explains why new branches of data science must steer from the impulse to measure correlation and instead seek to explore causality.
New discoveries in causality built upon big data can then be used to help people break bad habits and steer clear of harmful behaviors.