I’ve been taking the time to read up on Big Data topics and related technologies the past couple of weeks, so I thought I’d take the time to share with you my thoughts on some of the Big Data books I’ve been reading.
The first book I started was Taming The Big Data Tidal Wave by Bill Franks (John Wiley & Sons, ISBN: 978-1-118-20878-6). This is an introductory text and a nice place to start to get introduced to the terms, ideas, and technologies of Big Data. The book is broken down into three distinct parts.
The first part of the book is titled “The Rise of Big Data” and it consists of the first three chapters. This section of the focuses on defining Big Data and offers up some examples. The information is presented clearly and can serve as a useful introduction to the high level concepts of Big Data.
Part Two of the book focuses on the technologies, processes, and methods used by Big Data implementations. The book bogs down a little bit in this section as it tries to clearly explain predictive analytics. The examples are nice, but the book would benefit from a bit more in the way of definition and explanation.
The third and fourth parts of the book discuss the “people aspect” of Big Data. As with most IT projects, the human resources factor is crucial to success. The author does a nice job of discussing how to build a good team and foster an appropriate culture with respect to Big Data initiatives.
For a high-level, broad view investigation of Big Data, Taming The Big Data Tidal Wave by Bill Franks is well worth reading.
The second Big Data book on my reading list is Ethics of Big Data by Kord Davis (O’Reilly, ISBN: 978-1-449-31179-7). In my opinion, ethics is a topic that does not come up frequently enough in the world of IT. This short book – only 64 pages long – does a nice job of raising the ethical issues associated with managing large volumes of data… and the conclusions that can be drawn from that data.
Just a little bit longer than a white paper, the book is an easy read and will capture your interest with examples, anecdotes, and stories drawn from recent news and events. The author liberally provides web links for further investigation and reading where appropriate.
This little book is an important addition to the Big Data literature and should be standard reading for all management and project team members before they embark on Big Data projects. It will give you a lot to think about.
Next up on my Big Data reading list is NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence by Pramod J. Sadalage and Martin Fowler (Addison-Wesley, ISBN: 978-0-321-82662-6). Although not directly about Big Data, NoSQL database systems are commonly used in Big Data implementations, and NoSQL Distilled provides a concise but thorough introduction to the many forms of NoSQL offerings.
The book tries to pull together and explain the many disparate technologies and data models that fall within the NoSQL realm. And it does a reasonable job at doing so. The authors focus on four data models – key-value, document stores, column stores, and graph databases – and explain the characteristics of each. Given the inherent overlap between these models it can get confusing, but the book is easy to follow and after reading it you will come away with a better understanding of NoSQL and its place within IT and Big Data.
Over the course of about 150 or so pages, NoSQL Distilled does exactly that – it distills down the essence of what is meant by NoSQL and offers up concise, useful explanations coupled with guidance on when to use each of the various data models. And examples are even provided using a representative product for each of the data models.
Another book on my reading list, that I have not started yet, is MongoDB and PHP by Steve Francia (O’Reilly, ISBN: 978-1-449-31436-1). MongoDB is an example of a document store, NoSQL database system.
With all of these books under my belt, I am feeling much more confident about my knowledge of Big Data… but there is a lot to learn, and I am sure that I will be reading even more Big Data related titles over the coming months. So stay tuned… I may have more for you soon!