Missing data handling is typically done in an ad-hoc way. Without understanding the repurcussions of a missing data handling technique, approaches that only let you get to the "next step" in your analytics pipeline leads to terrible outputs, conclusions that aren't robust and biased estimates. Handling missing data in data sets requires a structured approach. In this workshop, we will cover the key tenets of handling missing data in a structured way