Book review: Agile Data Science

Agile Data Science

By Russell Jurney

Publisher: O’Reilly Media

Release Date: October 2013
Pages: 178

The title of this book, “Agile Data Science”, can easily draw a reader’s attention. On the one hand, the book provides a comprehensive overview of the data science technics; on the other hand, the emphasis is simultaneously laid on the agile methodology of software development. Furthermore, it touches upon another important aspect: how to work with Hadoop.

This small-sized book is easy to read. It has an easy-to-use and well-structured table of contents, which is very useful for the users who want to read only the particular or specific chapters. Structurally, the book consists of two parts: Main theory & Data Processing and Visualization. Chapter 3 in Part I, i.e. “Agile Tools”, describes the main technologies for the big data processing. Additionally, a user can find out not only how to use some of them, but how do they work and how to install them as well. By saying “agile”, the author does not speak about the agile methodology as such, he means that the applied tools and software makes a process agile. Part II is more about building charts for visual representation of the received results.

In general, this book is good for developers and those who are interested in Data Science and Big Data but have never worked in that area. It comprises a good technology stack and dwells on how to use it. More experienced people most probably will not be eager to read this book from start to the end, but can find useful some reasonable pieces of advice for their future projects.