This book introduces a collection of the most important fundamental concepts of data science. Some of these concepts are “headliners” for chapters, and others are introduced more naturally through the discussions (and thus they are not necessarily labelled as fundamental concepts). The concepts span the process from envisioning the problem, to applying data science techniques, to deploying the results to improve decision-making. The concepts also undergird a large array of business analytics methods and techniques. Throughout the book a number of fundamental data science principles, are described along with the illustration of each with at least one data mining technique that embodies the principle. For each principle there are usually many specific techniques that embody it, so in this book we have chosen to emphasize the basic principles in preference to specific techniques. It is believed that explaining data science around such fundamental concepts not only aids the reader, it also facilitates communication between business stakeholders and data scientists. It provides a shared vocabulary and enables both parties to understand each other better. The shared concepts lead to deeper discussions that may uncover critical issues otherwise missed.