The Executive Guide to Data Science and Machine Learning

A lot of jargon is thrown around within data science departments and in the leading business news sites these days, and there's a big hiring scramble across industries to develop advanced analytics to aid in decision-making. But what is important to know as an executive? While data science and the data economy are rapidly emerging and evolving fields, much of the work and new developments related to these fields fall into a few general principles and concepts. This guide aims to provide a short overview of key data-related topics and terms commonly used in data science today along with examples of how they are used in data science. Big data is a catch-all term for data that is large enough to cause issues in storage and analysis, marked by high volumes (lots of records), high degree of variety (text data, video data, and numerical data together), velocity (streaming data), and veracity (quality of data).