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The book is a tour-de-force of computational techniques most commonly required in data analytics. In a nutshell, this book which is the first-of-its-kind in data analytics in general (and not restricted to business analytics as the book title might suggest) is a "must have" and "must read" for all data analytics practitioners, and makes for an outstanding text book at the upper undergraduate and graduate levels. The language is simple and lucid. The book provides a welcome de-mystification of the essential and commonly used jargon in data analytics, by providing easily digestible definitions and examples of Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics. The book is computer language agnostic, and instead focuses on describing salient algorithms employed in data analytics.
One of the many hallmarks of this book is that every concept be it borrowed from systems theory, artificial intelligence and machine learning, statistics, decision theory, data structures, or from the plethora of subjects whose fusion forms the fast emerging subject of data analytics, is either preceded or accompanied by a brief but thorough and concise description and discussion of the essential mathematical tools required and most commonly utilized. This is often accompanied by examples to describe the mechanics and utility of the subject matter, whenever required. This book is possibly the first one of its kind that I have encountered in data analytics which not only explains the “know how” of the subject matter, but also tries whenever and wherever possible to explain the “know why” specific computational methods are employed. I strongly recommend this book to any serious student and practitioner of this rich and ever growing field of activity.