This book serves as a resource for people in non-technical roles who want to truly understand the relevant technology by providing an in-depth understanding of analytics concepts. The book begins with the “business side” of the subject: the problems that data scientists solve, how they fit into an organization, and how to hire and manage them. The rest of the book is concerned with technical topics - both analytical techniques, and the key technologies used. In each case the author explains the core concepts, why they are useful, and the assumptions or constraints that they entail. Each technical chapter concludes with a “problem set”, which are realistic scenarios (or real ones, drawn from the author’s experience) where technical knowledge is required to make a business decision. Answers and explanations are provided. This book is a perfect background for executives who make crucial decisions based on analytics, managers who hire data scientists and need to assess their technical work, and salespeople who need to explain what an analytics product does. However, it is also excellent for data scientists themselves. It is very easy to get lost in the weeds of data cleaning or model tuning; this book gives a big-picture view of what these details mean for the real-world applications they ultimately support.