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Top 10 Essential Books for the Data Enthusiast


A unique top 10 list of book recommendations, for each of 10 categories this list provides a top paid and top free book recommendation. If you're interested in books on data, this diverse list of top picks should be right up your alley.



The true data enthusiast has a lot to read about: big data, machine learning, data science, data mining, etc. Besides these technology domains, there are also specific implementations and languages to consider and keep up on: Hadoop, Spark, Python, and R, to name a few, not to mention the myriad tools for automating the various aspects of our professional lives which seem to pop up on a daily basis. There are a lot of topics to keep abreast of. Fortunately (unfortunately?) there is no shortage of books available on all of these subjects.

There are a lot of lists available of the top books in particular categories related to data. In fact, KDnuggets has previously, and rather recently, put together such lists on data mining, databases & big data, statistics, AI & machine learning, and neural networks. But these were based on Amazon top sellers in narrow categories, without editorial discretion or consideration for freely-available content and e-books.

First off, let's get this out of the way: the title of this post is misleading. This inclusive list of essential books for the data enthusiast (or practitioner) recommends a top paid and free resource in each of 10 categories. Let's face it: though we may work or be otherwise directly involved in a limited number data avenues, we generally tend to have an understanding of a greater number of these avenues, as both a practical matter and one of interest.

So, while a Hadoop expert may not need expert-level insight into deep learning, chances are that they have a more-than-passing interest in the subject. This post is a chance to solidify these interests and provide material suggestions for the data enthusiast looking to widen their knowledge base.

Editor's note: It is important to point out that KDnuggets receives no incentive, financial or otherwise, related to any of these recommendations, nor does it take part in any affiliate sales programs. These recommendations are made solely in the interest of our readers.

Keep in mind that there may be overlap in many of these categories, which is inevitable (see: The Data Science Puzzled, Explained). Often the focus of the material determines its categorization, as opposed to simply the material itself.

Books"

Data Science

Top Paid Recommendation: Data Science for Business

When trying to learn about a new field, one of the most common difficulties is to find books (and other materials) that have the right "depth". All too often one ends up with either a friendly but largely useless book that oversimplifies or a heavy academic tome that, though authoritative and comprehensive, is condemned to sit gathering dust in one's shelves. "Data Science for Business" gets it just right.

- m l, Amazon Review.

Top Free Recommendation: The Art of Data Science

This book describes the process of analyzing data in simple and general terms. The authors have extensive experience both managing data analysts and conducting their own data analyses, and this book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science.

- Official Website

Big Data

Top Paid Recommendation: Big Data: Principles and Best Practices of Scalable Realtime Data Systems

I have rarely seen a thorough discussion of the importance of data modelling, data layers, data processing requirements analysis, and data architecture and storage implementation issues (along with other "traditional" database concepts) in the context of big data. This book delivers a refreshing comprehensive solution to that deficiency.

- Kirk D. Borne, Amazon Review

Top Free Recommendation: Big Data Now: 2015 Edition

In the four years that O’Reilly has produced its annual Big Data Now report, the data field has grown from infancy into young adulthood. Data is now a leader in some fields and a driver of innovation in others, and companies that use data and analytics to drive decision-making are outperforming their peers.

- Official Website

Apache Hadoop

Top Paid Recommendation: Hadoop: The Definitive Guide

I appreciate that this book covers high-level concepts as well as dives deep into the technical details that you will need to know for the design, implementation and day-to-day running of Hadoop and its various associated technologies.

- Al Gordon, Amazon Review

Top Free Recommendation: Hadoop Explained

Hadoop is one of the most important technologies in a world that is built on data. Find out how it has developed and progressed to address the continuing challenge of Big Data with this insightful guide.

- Official Website

Apache Spark

Top Paid Recommendation: Learning Spark

The information that is available on the Internet is great, but this book brings much of it together in one place. If you want to learn to think like a Spark programmer--*not* the same as thinking like a programmer--this is the place to begin.

- Brian Castelli, Amazon Review

Top Free Recommendation: Mastering Apache Spark

This collections of notes (what some may rashly call a "book") serves as the ultimate place of mine to collect all the nuts and bolts of using Apache Spark. The notes aim to help me designing and developing better products with Spark.

- Official Website