In the first part of this series, I discussed how important it is as a data scientist to ask the right questions when solving a new problem. In this post I will be digging into a specific example relating to the situation when a data scientist is presented with data to explore.
Specifically, we will be looking a dataset from a calling card company that was experiencing issues with fraud. But first, let’s review the key questions that should be answered when beginning any problem like this one.
Author: Scott W. Strong