Book Review: Big Data by Viktor Mayer-Schonberger & Kenneth Cukier


DATA. The name of the character from the Star Trek: Next Generation television series and movies[1]. Played by actor Brent Spiner, Data represents an outsider’s view of humanity as well as a futuristic possibility of the combination of the best of man and machine to achieve goals with empathy checked by logic and the need for efficiency and accuracy. Data is also known as a grouping of information that can be analyzed for decision-making. Data, the character, had a memory capacity of 800 quadrillion bits (~89 Petabytes)[2]. We, as data producers, created “2.8 zetabytes of [data] in 2012, a number that’s as gigantic as it sounds, and will double again by 2015.[3]” How many Datas do we need to hold our data if that was even an option?

Big Data,” according to Mayer-Schonberg and Cukier, is “the ability of society to harness information in novel ways to produce useful insights on goods and services of significant value.[4]” Even though this definition appears lofty, the book is actually more grounded as it presents the benefits, the promises, the potentials, and the risks of big data to our businesses, our lives, and our society. They begin with describing the new mindset that allows big data to fulfill its promises: we must accept that more data is better than less, that messy data is good, and that correlation, not causality, is good enough. The key to big data is that it “is about what not why – we can discover patterns and correlations in the data that offer us novel and invaluable insights.[5]

Based on some prior successes of big-data techniques (like airflight price discounts, hotel discounts, the Google flu algorithym) a big data consciousness – “the presumption that there is a quantitative component to all that we do, and that data is indispensible for society to learn from[6]” has evolved.   And they do mean everything we do, especially our interactions online via social media and other interactive online platforms and mobile apps. Now “our personal connections, opinions, preferences, and patterns of everyday living have joined the pool of personal information already available about us.[7]” But one of the problems is the insidious nature that this recording of our everyday activity takes place. “Technology has reached a point where vast amounts of information often can be captured and recorded cheaply. Data can frequently be collected passively, without much effort or even awareness on the part of those being recorded.[8]

Why is this data so valuable? Presented in the book is the nature of the data itself: it can be reused for many purposes not just the one it was collected for, the quality of the data does not diminish with its use, ad storage and processing of the data has decreased in cost significantly.

But what about the issues of privacy and intellectual property ownership? What about notice and consent and our right to not be monitored 24/7? The book offers some insight into these concerns and some possible solutions, like making the data collectors and users more accountable to those they collect the data from. It is easier said than done. However, it was nice to see the authors tackle the questions instead of glossing over them.

There is a lot to chew on in this book. Much more than we can recap in this review. It serves as a great primer on big-data for those who want to get a good foundation on its essence, but it also serves as an exploratory for those who want to delve more into big data’s long-term impact. I recommend you read it and then engage with it. I found myself halfway through the book starting to see big-data applications to a lot of what my clients are doing right now. Was that one of the purposes of the book? Isn’t that the purpose of any non-fiction book? To make us stop, look around, and think, and then…

For more on this book:


[1] Yes, I am a sci-fi buff and enjoy Star Trek, Star Wars, etc. But I do not reach the level of “trekky.” It is, however, a goal that can still be achieved.

[2] “Data,” Memory Alpha,, (accessed March 10, 2014).

[3] Patrick Tucker, “Has Big Data Made Anonymity Impossible?” MIT Technology Review,, May 7, 2013.

[4] Big Data, pg. 2

[5] Big Data, pg. 14

[6] Big Data, pg. 97

[7] Big Data, pg. 100

[8] Big Data, pg. 101

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