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on 15 September 2013
This is a book about the impact of digital technologies on statistical forecasting. It is quite general in scope and aimed largely at the lay reader. It contains some insights but the main points are often quite simple: e.g. data correlations can have surprising results, large companies such as Google hold lots of data and this makes them powerful, data retention has its dangers etc... The main point of the book, that improved data collection will impact greatly on society is well presented and the book overall is a worthy and easy read.
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on 5 May 2013
My issue with Big Data is that it does not take big data seriously enough. Although the authors have pedigree (Editor at the Economist; Professor at Oxford) this is not an academic text: it belongs to that category of popular essays that attempt to stimulate debate. Anyone who works with data (e.g. technologists, scientists, politicians, consultants) or questions what will be borne from our age of data affluence may have expectations for this book - unfortunately it falls short on providing any real answer.

The book paints an impending revolution in mighty strokes. The authors claim the impact of data-driven innovations will advance the march of humankind. What they end up presenting is a thin collection of happy-ending business stories -- flight fare prediction, book recommendation, spell-checkers and improved vehicle maintenance. It's too bad the book's scientific champion Google Flu Trends, a tool which predicts flu rates through search queries, has proven so fallible. Last February it forecast almost twice the number of cases reported by the official count of the Center for Disease Control.

Big data will certainly affect many processes in a range of industries and environments, however, this book gestures at an inevitable social revolution in knowledge making (`god is dead'), for which I do not find coherent evidence.

The book correctly points out that data is rapidly becoming the "raw material of business". Many organisations will tap into the new data affluence, the outcome of a long historical process that includes `datafication' (I'll define later) and the diffusion of technologies that have tremendously reduced the costs involved in data production, storage and processing.

So, where's the revolution? The book argues for three rather simplistic shifts.

Read the rest of the piece on the LSE Review of books, at bit. ly/bigdatareview
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on 15 June 2013
I first met Kenn Cukier when he was the Economist correspondent in Tokyo, at the time of the Olympus scandal. Kenn enthusiastically told me about his ideas for 'Big Data' and I was honest but unintentionally hurtful in explaining that I believed there would be little general interest in what I thought was a rather dry subject. How splendidly wrong I turned out to be, and after reading `Big Data' over the last week, now have an informed understanding of the enormous potential for good but also bad that data mining provides. In a week where we learned of Edward Snowden's disturbing revelations, every thinking person should read this insightful and elegantly written book.
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on 11 March 2013
*A full executive summary of this book is available at newbooksinbrief dot com.

The main argument: Statistical information, or data, has long been recognized to be a potentially rich and valuable source of knowledge. Until recently, however, our ability to render phenomena and events in a quantified format, store this information, and analyze it has been severely limited. With the rise of the digital age, though, these limitations are quickly being eroded. To begin with, digital devices that record our movements and communications, and digital sensors that record the behavior of inanimate objects and systems have become widespread and are proliferating wildly. What's more, the cost of storing this information on computer servers is getting cheaper and cheaper, thus allowing us to keep much more of it than ever before. Finally, increasingly sophisticated computer algorithms are allowing us to analyze this information more deeply than ever, and are revealing interesting (and often counter-intuitive) relationships that would never have been possible previously. The increasing datification of the world, and the insights that this is bringing us, may be thought of as one grand phenomenon, and it has a name: Big Data.

The insights that are emerging out of big data are spread out over many areas, and are already impacting several aspects of society. To begin with, big data is helping established businesses to run more efficiently and safely. For example, big data is being used to streamline assembly lines and also to catch quality control problems in the factory. But the benefits of big data go well beyond the factory. For example, the courier company UPS has used big data to help it map out more efficient trucking routes. The resulting improvements have allowed UPS to shave 30 million miles and 3 million gallons of fuel per year from their routes (loc. 1352). The more efficient trucking routes have also led to less traffic accidents. Meanwhile, car companies are beginning to use data from sensors in automobiles to understand which parts are causing problems, and also to understand where and why accidents are happening, so that they may be lessened.

In addition to helping already established businesses, big data is also allowing for new business opportunities that were never possible before. For example, the business prodigy Oren Etzioni used big data to set up a business called Farecast that predicts the cost of airfare tickets. When his business was bought by Microsoft for $110 million, Etzioni used big data again to set up a related business that predicts the cost of all manner of consumer goods. His very profitable business, Decide.com, saves consumers on average $100 per product (loc. 1867).

Outside of the business world, big data is also being used by governments to help reduce costs and make society safer. For example, in 2009 Google was able to apply big data to search terms to help identify how the H1N1 virus was spreading through communities in real time. This method of tracking disease pandemics holds great promise for allowing public health organizations to know when pandemics are beginning, and also to keep better track of how they are unfolding, in order that they may better contain them. In addition, big data is being used to help identify where potentially dangerous infrastructural problems are occurring, and also to identify trouble spots for fire hazards, in order that they may be addressed.

Big data also has significant potential uses in health care. Indeed, our increasing ability to monitor and record everything from our vital signs to the health of our systems to our individual genomes promises to inaugurate an age of personalized medicine that will allow doctors to more easily diagnose our ailments and tailor treatments to our individual bodies.

While big data may already be bringing us impressive benefits, Viktor Mayer-Schonberger and Kenneth Cukier argue that the bulk of the benefits are yet to come. Indeed, for the authors, businesses and governments are only just now waking up to the incredible potential of Big Data. And as they direct more attention to recording and analyzing data streams, the potential uses of the information will only multiply.

On the negative side, big data also carries substantial potential dangers. Most notably, as more and more information about us is recorded, kept and used, our privacy is increasingly threatened. For the authors, a good deal of oversight will be needed in order to ensure that the potential abuses of big data are curbed.

The book is well written and represents a fine overview of the present and future of big data. Also, the authors do well to raise important big-picture issues related to the phenomena, though the potential impacts of big data (both positive and negative) are occasionally overblown. All in all the book is a good introduction to an important and interesting topic. A full executive summary of the book is available at newbooksinbrief dot com; a podcast discussion of the book will be available soon.
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on 8 June 2013
If you know absolutely nothing about Big Data and want to know what the new Buzz word in town is about then this book provide a good high level view. The bad news is that the book concentrates on *what* Big Data is about and ignores the *how* and the *why*. A bit of history about how Big Data came to be would have been nice. Instead the book gives us plenty of examples of Big Data being used. These all tend to be "Company X discovered a correlation between fact Y and fact Z that you probably wouldn't have expected". The point being we are not longer supposed to question why there is a link between Y and Z; the data is supposed to speak for its self. No justification for this point of view is ever given (none of the examples described why the researchers came to their conclusions).

This book could be used as an introduction to Big Data, but if you are expecting to come away with a detailed knowledge of any part of the subject you'll be disappointed.
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on 22 July 2013
I finished this book this weekend, out of a misguided sense of obligation, and just found myself annoyed. Compared to classics such as the Signal and the Noise or even Moneyball, this book doesn't have much to offer either as useful details or new insight. It reads as a long series of anecdotes, which anybody who keeps half-way current with the popular press will have already heard about. I suppose it could serve as an introduction of sorts, although I'm not sure for whom - i wouldn't recommend it to a technologist, and any businessperson with concerns in IT should already know this stuff.
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on 30 April 2013
It's an OK book, and I enjoyed reading it to get a general idea of what is possible, but that's about it. There's little more than "Look! See how company XYZ came up with this really cool application of big data?", over and over and over.
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