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Big data computing
Akerkar R., Chapman & Hall/CRC, Boca Raton, FL, 2014. 564 pp. Type: Book (978-1-466578-37-1)
Date Reviewed: Apr 22 2014

This book is an edited collection of chapters on big data. As such, it appears on a minefield of conceptual challenges. First, big data is as hot as it is poorly defined. It is a staggering amount of messy data that captures the imagination as much as it defies description. Some merely define it as the phenomenon that is occurring as the amount of data generated by digital applications jumps by orders upon orders of magnitude. Some define it in terms of the technology needed to process enormous volumes of data, such as Hadoop. Some define it in terms of the existing database technology, which can no longer handle either the volume or the complexity, and still others will use the term to include all the data that has ever been created or has yet to be created.

In response to this emerging phenomenon there is a whole flock of new books on big data, all of which attempt to capitalize on the hype and popularity of the buzzword. So, stepping into the big data arena with another contribution to the confusion has its risks.

In addition, being an edited book of chapters provides a second strike against it. While there are some notable and impressive exceptions, edited books are generally of rather poor quality. This is because the editor does not hold the individual authors to the standard necessary for a quality volume. Chapters are generally uneven in quality and level of detail. They are written in different styles addressing different audiences, and often the authors are just looking for an outlet for a paper that would have had little chance of finding acceptance in a journal.

I provide this context because this book is exactly what you would expect within such a context. The book consists of 17 chapters that suffer from the flaws just mentioned. There is little that can be said about the book in general. There is a lot of variety in the topics, both within and across chapters. The book does not really have a coherent conceptual structure. Nor do most of the chapters. There is a lot of overlap between chapters, and a lot of the material consists of general topics about data, data management, and data analysis that are not specific to big data. Finally, most of the information in the book will be out of date fairly quickly.

Having said that, is there anything redeeming about this volume? The answer is yes. It does show a breadth of perspectives from which big data is currently being considered. It provides our thinking during a fleeting moment in time as the big data phenomenon evolves. Each chapter provides a rich set of topics and a rich set of references for the topics being discussed.

Individuals with specific interests might find specific chapters to be of greater value than others. I found the book online, which interested readers can do as well by simply Googling the title. You can download specific chapters, and if there seems to be sufficient merit in getting the entire collection you can order a bound copy.

Reviewer:  J. M. Artz Review #: CR142205 (1407-0514)
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