Analysis Documentation

Randy Au, Quant User Researcher, Google

Randy advocates that data documentation makes the work of data scientists easily traceable and reproducible. This is particularly important when working on ad-hoc analysis requests, as it is easy for output to end up in a temporary directory with little context. There are several ways to package analysis deliverables, including Excel files, CSV files, slide decks, dashboards, and shared documents, in order to make them free-standing and easily traceable.