Written by two experts in the area (a third expert, Soumendra Mohanty, is listed as the technical reviewer), I was impressed with the simplicity of the organization of the book. It is written like a mini help guide to big data-related subjects. The title accurately represents the content. The target audience is not technical developers, but high-level managers, decision makers, and enterprise and software architects.

It is organized in a question and answer format, providing a good resource for the reader. With this book at hand, the reader will be familiar with the general terminology of big data problems and analytics, popular architectural solutions, various classes of tools and industries serving the layered architecture, issues concerning cloud-based solutions, and the nature of big data processing in terms of size and speed. A popular technology, Hadoop, and additional distributed database and analytics layers are also addressed. The pros and cons of proprietary solutions are outlined.

The book starts with an introduction to big data (chapter 1). This is followed by chapter 2, “Big Data Application Architecture,” in which overall architectural issues are addressed, including Hadoop layers and big data applications. In the third chapter, “Big Data Ingestion and Streaming Patterns,” multisource multidestination protocol converter patterns are addressed, among other topics. “Big Data Storage” and “Big Data Access Patterns” are covered in chapters 4 and 5, and chapters 6 and 7 are reserved for “Data Discovery and Analysis Patterns” and “Visualization Patterns.” In chapter 8, “Big Data Deployment Patterns,” cloud and hybrid architecture issues are addressed. Nonfunctional requirements are covered very well in chapter 9, which includes security aspects. I most liked chapter 10, which introduces big data case studies such as environment change detection and real-time traffic monitoring. Chapter 11 is on “Resources, References, and Tools.” The book ends with a reference list and a well-developed index.

The back cover claims: “The book deals with various mission critical problems encountered by solution architects, consultants, and software architects while dealing with the myriad options available for implementing a typical solution.” This is an accurate description in a nutshell of what one can get out of this book.

I personally learned from the book even though I am an expert in some areas of big data-related research and development. I would recommend it as a “first read” for anyone looking for a quick understanding of how to deal with large heterogeneous and unstructured data processing problems and solutions.

The need for big data analytics is here. However, there are no turnkey solutions offered yet due to the multidisciplinary nature of the problem at hand. In the meantime, responsible decision makers need to educate themselves in this area. This book would be good place to start.

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