Today's world is increasingly characterized by internet-availability of massive open datasets, repositories teaming with fresh algorithms, around-the-clock market data feeds, and many forms of scalable, web-integrated NoSQL datastores. Joan discusses a "Lean Data Analysis" approach to managing a Big Data project when the tools available include: a desktop equipped with net connectivity, MATLAB, and a freely-available NoSQL datastore (MongoDB).  Anecdotal examples and results are demonstrated first-hand, reflecting one data scientist's journey to train and test an improvised ML model over billions of data points and then benchmark-test the fitted model against competing algorithms.