This book is mistitled, probably to take advantage of the demand for titles in big data. In the first place, I don’t believe there are any “fundamentals” to big data in the way that normalization and ACID (an acronym for atomicity, consistency, isolation, durability) transaction models are fundamental to the relational data model. In the second place, if the goal was to use “big data” in the title, it should have been called A survey of concepts and buzzwords related to big data.

The five Vs are briefly explained (yes, there are five now, sometimes six). There is a paragraph on NoSQL and one on NewSQL, which was new to me. Hadoop got a brief nod. Other than that, the bulk of the book is a conglomeration of data topics not at all specific to big data and certainly not fundamental. Online analytical processing (OLAP); online transaction processing (OLTP); and extract, transform, and load (ETL) are mentioned, which are data warehousing concepts. And the ACID transaction model is mentioned, which belongs to the relational model. The problem with mentioning these items is that the book makes them appear to be part of the big data paradigm, when in reality big data is often defined as data that is so voluminous that it can’t be handled by existing data paradigms. So, glopping them together is conceptually misleading. There is also mention of numerous analytical techniques, which really belong to analytics, statistics, or data mining, but are not unique to big data.

Despite the paradigmatic confusion that characterizes the book throughout, it does have redeeming value. Practitioners are often confronted with a flurry of new buzzwords and are more concerned with what the buzzwords mean than what paradigm they belong to. And they don’t want detailed technical explanations. They just want to get the gist of the ideas. For those people, this is the book they are looking for. The authors wade through a sea of buzzwords, explaining each one in simple conversational terms. Maybe you won’t know why the ACID transaction model is a problem for big data, but you will have a general idea of what it is.

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