Few things in business analytics have gotten the excitement and, yes, the hype as Machine Learning. It fires up the imagination of every sci-fi loving data scientist, with images of true thinking computers adapting and learning new tasks on their own. The good news is that Machine Learning works and it can indeed do all of that. The bad news is that it can’t do those things as well, as fast or as easily as the hype suggests. There are quite a few things that Machine Learning can do quite well, such as signal identification and noise removal based on both structured and unstructured data. But there is also a list of things that Machine Learning in 2017 CANNOT do, things such as automated complete data cleaning. Another thing Machine Learning can’t yet do is replace humans.

And yet, far too many data scientists today insist on using Machine Learning in areas where it makes little sense. And that frustrates today's guest. Jitendra Papneja has worked in analytics for multiple Fortune 100 companies and today serves as an analytics leader for a Fortune 100 consumer goods company.