Month: July 2017

This question comes up often.

It is typically asked by starting data scientists, analysts and managers new to data science. Their bosses are under pressure to show some ROI from all the money that has been spent on systems to collect, store and organize the data (not to mention the money being spent on data scientists).

Sometimes they are lucky – they may be asked to solve a very specific and well-studied problem (e.g., predict which customer is likely to cancel their mobile contract). In this situation, there are numerous ways to skin the cat and it is data science heaven.

But often they are simply asked to “mine the data and tell me something interesting”.

Where to start?

This is a difficult question and it doesn’t have a single, perfect answer. I am sure experienced practitioners have evolved many ways to do this. Here’s one way that I have found to be useful … (read the rest of the post on Medium)