Best Books on Big Data & Data Science

In this article, we’ll recommend books and other resources specifically about big data and data science.

(This article is part of our Tech Books & Talks Guide. Use the right-hand menu to navigate.)

Big Data: A Revolution That Will Transform How We Live, Work, and Think

Authors: Viktor Mayer-Schonberger and Kenneth Cukier

Big Data: A Revolution provides a broad overview of big data and the impact that it’s making on modern society. While by no means a technical book, it does provide a good high-level introduction to what big data is and how it’s affecting practices in areas as diverse as:

• Fraud detection
• International law enforcement
• Linguistics
• Automated language translation

Well-suited for business managers and analysts, or maybe even C-level executives, Big Data: A Revolution provides insight and guidance on how industries should move forward in the wake of today’s information revolution.

One of the book’s central premises is the notion of “why, not what”. For example, the book states:

“The era of big data challenges the way we live and interact with the world. Most strikingly, society will need to shed some of its obsession for causality in exchange for simple correlations: not knowing why but only what.”

Hadoop: The Definitive Guide, 4th Edition

Author: Tom White

Hadoop: The Definitive Guide is a big data book that’s targeted at technical audiences. The book was originally published in 2009 and is currently sold as a 4th edition update.

Praised by developers and data engineers the world-over, Hadoop: The Definitive Guide provides how-to’s on building and maintaining distributed, parallel processing data systems with Apache Hadoop (HDFS, MapReduce, and YARN). The 4th Edition update even goes into details on Hadoop 2 deployment, including technical details that you should know about YARN, HBase, Parquet, Flume, Crunch, Pig, Hive, and Spark.

The book also presents interesting case studies from the healthcare and genomic sciences industries.