This document provides an overview of data science including its importance, what data scientists do, how the field has emerged, and how to become a data scientist. It discusses how data science can help answer important business questions using LinkedIn in 2006 as a case study. It also outlines the typical data science process of framing questions, collecting and cleaning data, exploring patterns, and communicating results. Finally, it introduces some common data science tools like SQL, analytics software, and machine learning algorithms and discusses options for continuing education in data science.