This book is envisioned as a companion volume on modern cloud computing. However, it is too broad, and in my opinion provides only superficial coverage of many subjects. It is certainly a deliberate (and courageous) decision by the authors. Clearly, breadth versus depth is an optimization problem for any writer. Therefore, in this case, the most depth should be concentrated around modern cloud computing, yet by chapter 5 the reader is left with the realization that the optimization process simply does not take place. Strictly speaking, only chapters 10, 14, and 15 try to deliver on the promise of the title--unfortunately, too little, too late.

The authors are trying to describe the modus operandi of a contemporary programmer or data scientist who deals with big data, machine learning, and applied statistics (deep reinforcement learning and transfer learning are conspicuously missing). As such, the book reflects more on the authors’ experiences in the field and does not attempt to come up with a more unified theme. (An overarching design or machine learning archetype could have been, for example, amalgamating all the code snippets in different languages.)

An opportunity was missed. Consequently, the sequence of chapters looks quite incidental to the subject. If it were really an introduction to the data industry, it would need to cover the essentials, but at the same time address the mathematical principles and archetypes in enough depth. Then, things that require mandatory understanding would be emphasized.

In my opinion, the book simply does not deliver on that particular premise. The price of self-containment is too high, and the intended audience is too broad. Yet this is not an encyclopedia; the level of exposé varies substantially, leaving bewildered readers to comprehend what they have really learned.

Perhaps the authors explain it best in the introduction:

This is not your typical introduction-to-data-science book; it’s a handbook that guides you through a journey to explore various topics and takes you through many roads to the goal you set each time you pick up the book.

Hopefully, readers looking for direction in the data industry will find the process useful.