Big Data Fundamentals: Concepts, Drivers & Techniques

Thomas Erl, Wajid Khattak, Paul Buhler

Published by

Pearson

ISBN

978-0134291079

RRP

£24.99

Reviewed by

Patrick Hill MBCS CEng CITP

Score

10 out of 10

Modern business systems accumulate huge amounts of data from diverse application domains. Big Data is an interdisciplinary branch of computing which is concerned with various aspects of the techniques and technologies involved in exploiting these very large, disparate data sources.

The eight chapters of this book are organised into two sections which together provide a high-level overview of the Big Data landscape.

The first section is concerned with Big Data in the business. In this section, the principal concepts and terminology of Big Data are introduced along with high-level discussion of the kinds of problems that Big Data can help to solve and the general approaches to these solutions.

The section outlines a Big Data analytics lifecycle with which businesses may begin to incorporate Big Data into their processes in order to derive value from their data sets. The section closes with a brief review of the roles and limitations of the typical data processing components that are present within modern businesses and identifies where Big Data fits into this.

Having focussed in the first section on the “what?” and “why?” of Big Data, the second section goes on to consider the “how?”, by discussing the principal concepts and technologies that underpin Big Data implementations. As the book describes, the volume and variety of data involved in Big Data projects has wide ranging implications for data storage, processing and analysis.

The book outlines approaches to distributed data storage, the limitations and trade-offs that have to be made, as well as describing techniques for storing non-relational data using alternative database systems such as NoSQL and Graph databases. The book outlines the Map/Reduce approach to distributed batch processing and summarises common machine learning concepts and data visualisation techniques. The authors provide helpful summaries of each technology, giving the types of applications to which each is suited to as well as those to which they are not.

This is a brief, informative and very readable introduction to Big Data which enables the reader to quickly bring themselves up-to-speed on the key topics and issues as well as serving as a basis for further exploration of topics of interest. The book should attract a broad readership of business users and technologists.

Further information: Pearson

April 2016