Data Science's Most Used, Confused, and Abused Jargon

A global system of networked devices now generates terabytes of data each second. Affordable storage makes it possible to record seemingly arbitrary amounts of information. And machine learning algorithms, together with distributed computing, increasingly rise to the task of extracting actionable intelligence from this information. But what precisely does "big data" mean? As the importance of data science has grown, so too has the body of jargon associated with it.