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Reviewer: Burkhard Englert

Over the last few years, data analytics has emerged as one of the core areas of computer science. It provides us with powerful tools that allow us to process and understand the ever-increasing stream of information flowing from business and industrial processes, text and structured databases, images and videos, and physical and biomedical data. While many ready-to-use data analysis models and algorithms are easily available and do not demand expert knowledge from their users, their proper use nevertheless benefits from a solid understanding of the underlying ideas and principles. Providing this understanding is the goal of this excellent short book. Data analytics is often perceived as a somewhat intimidating field only open to experts with strong mathematical backgrounds. This book successfully aims to eliminate this preconception and potential fear, beginning with its less-than-intimidating size of only 150 pages. Instead of trying to cover everything, the author focuses on essential ideas and techniques, providing the reader with a very solid and easy-to-follow introduction to the basics of data analytics. After a brief introduction in chapter 1, chapter 2 discusses data and relations, followed in chapter 3 by data preprocessing. Chapter 4 concludes the introductory chapters with a description of data visualization techniques. Chapters 5 to 9 then discuss several fundamental data analysis techniques: correlation (chapter 5), regression (chapter 6), forecasting (chapter 7), classification (chapter 8), and clustering (chapter 9). The book also includes a brief appendix that reviews three optimization methods. When reading this book, it becomes clear that its content is based on lecture notes the author used when teaching courses on data analytics. Overall, the book greatly benefits from this history: chapters are concise and explain the underlying mathematical ideas of a particular technique without providing too much detail. I have one caveat, however: readers interested in learning how to implement these techniques should look elsewhere. There are no code examples or programming exercises. Nevertheless, for those planning to teach a course on data analytics or those looking for a reference to better understand basic analytic techniques, I wholeheartedly recommend consideration of this book. Online Computing Reviews Service