Being continually updated on new trends in computing through social networks and specialized publications, I must admit that the term “big data” has flooded the web over the last few years. I also witnessed the change of mood among people over time regarding what they think of big data. This ranges from the posts “Big data is the future,” to the funny pictures showing an evil character from Star Wars threatening anyone talking about big data again. Is big data worth talking about it? Certainly yes. So what is it? The authors of this book define it as “seeing and understanding the relations within and among pieces of information that, until very recently, we struggled to fully grasp.” Big data emerged as a natural trend following the huge advance in data processing and the flood of data available over the web.

The two projects mentioned in chapter 1 show good examples of the use of big data analysis in flu spread prevention by Google and in travel metasearch and price prediction by Farecast.com. The importance of these projects relies on their utility related to health and money.

In chapter 2, “More,” the authors remind us of the availability of a huge amount of data for analysis compared to previous times where any statistics were based on small sets. The availability of data, however, does come at a cost. It originates from input coming from human users, computers-generated data, and so on. It is therefore imprecise and sometimes corrupted. In chapter 3, “Messy,” the authors detail the messiness aspect of available data and the challenge it presents to the analysts.

When working with a large amount of data, any finding or insight originates from a correlation between that data and some facts. “Correlations let us analyze a phenomenon not by shedding light on its inner workings but by identifying a useful proxy for it.” Chapter 4 discusses correlation and states that it is not necessarily an announcement of the death of theory but in some cases a catalyst toward highlighting new theories.

In chapter 5, “Datafication,” the authors discuss the fact that many things might serve as data, including words, location, and interactions. Although, not all data is meaningful for a given analysis. In this direction, chapter 6 details the latter aspect, “data value.”

An important question is raised in chapter 7, “Implications.” In this chapter, the authors predict the effect of using big data. This includes data licensing, the impact on our privacy, and our sense of freedom. The latter aspects are detailed in chapter 9, “Control.” Chapter 10, “Next,” summarizes some predictions related to the big data trend.

The amount of historical facts and related anecdotes is impressive. They make the book’s content very accessible and fully put in context. I must admit, though, that I don’t agree with the authors on page 32: “The quest for exactitude began in Europe in the middle of the thirteen century.” This is biased and definitely wrong. This quest began a long time before that and somewhere other than Europe. It would be useful to refer to more accurate sources of information on the history of science for the next editions of the book.

Overall, the book is more appropriate for a nontechnical audience. It might need further updates given the fast-paced adoption of big data tools and technologies.

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