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Data warehousing in the age of big data
Krishnan K., Morgan Kaufmann Publishers Inc., San Francisco, CA, 2013. 370 pp. Type: Book (978-0-124058-91-0)
Date Reviewed: Dec 17 2013

Over the last 25 years, there have been significant changes in the capture, processing, dissemination, analysis, and use of information. This transformation has not only affected how we do business, but has also impacted the underlying techniques and technologies that make business possible. For example, the relational model that stores traditional business transactions is no longer adequate to meet the storage and manipulation challenges of such information. This book argues that big data, with its three key dimensions of volume, velocity, and variety, presents a challenge that data analysts can’t ignore.

The book is divided into three parts. The first part deals with the basic concepts of big data. The first chapter argues that unstructured data is now the norm for Internet-based applications such as social media (Facebook, Twitter, and so on), weather, and customer surveys and comments. Three subsequent chapters address how to work with big data, the processing architecture needed, technologies for distributing the processing workload (Hadoop and NoSQL), and novel filing systems (the Google file system (GFS), for example). Chapter 5 presents case studies on businesses that used big data to create better services for their customers.

Part 2 includes four chapters that provide an in-depth description and discussion of the second main theme of the book, data warehousing. The author recaps traditional warehousing technology, including the different generations of data warehousing, the challenges faced, and the evolution of the technology. This part then turns to the role of data warehousing in handling big data and what’s involved in reengineering to accommodate the additional challenges. Managing changes in workload and planning is a key aspect for processing and handling big data. The last chapter in this part will be of great interest to technologists and managers alike, as the author considers how new technologies such as cloud computing, data virtualization, and solid-state drives (SSDs) will affect data warehousing. The author concludes this part with a decent list of Internet resources for further study.

The last part details the building of a big data warehouse in five chapters, including the integration of big data into a warehouse, the architecture for storing and processing metadata and master data, the implementation of information life cycle management, the newly evolved role of the data scientist, and some available tools, such as data visualization and business analytics. Finally, in the last chapter, the author considers how to put these techniques into practice in real life.

Overall, I found the book easy to read and understand. It’s written from the perspective of a practitioner; as such, it is meant for a hands-on person. The author does not make any claims about the virtues of the book. Rather, he is quite humble: “The … goal of the book is to help you navigate through the complex layers of big data and data warehousing.” Further, he claims to provide “information on how to effectively think about using all these technologies … to design the next-generation data warehouse.”

More reviews about this item: Amazon

Reviewer:  Amit Rudra Review #: CR141816 (1402-0117)
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Data Warehouse And Repository (H.2.7 ... )
 
 
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