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Summary
Summary
A revelatory exploration of the hottest trend in technology and the dramatic impact it will have on the economy, science, and society at large.
Which paint color is most likely to tell you that a used car is in good shape? How can officials identify the most dangerous New York City manholes before they explode? And how did Google searches predict the spread of the H1N1 flu outbreak?
The key to answering these questions, and many more, is big data. "Big data" refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena--from the price of airline tickets to the text of millions of books--into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven't even done yet, based on big data's ability to predict our future behavior.
In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.
www.big-data-book.com
Author Notes
VIKTOR MAYER-SCHONBERGER is Professor of Internet Governance and Regulation at the Oxford Internet Institute, Oxford University. The co-author of Big Data: A Revolution That Will Transform How We, Live, Work, and Think , he has published over a hundred articles and eight other books, including Delete: The Virtue of Forgetting in the Digital Age . He is on the advisory boards of corporations and organizations around the world, including Microsoft and the World Economic Forum. KENNETH CUKIER is the Data Editor of the Economist and co-author of Big Data: A Revolution That Will Transform How We Live, Work, and Think . His writings on business and economics have appeared in Foreign Affairs , the New York Times , the Financial Times , and elsewhere.
Reviews (4)
Publisher's Weekly Review
Oxford professor Mayer-Schonberger (Delete: The Virtue of Forgetting in the Internet Age) and Economist data editor Cukier survey the changes to modern life created by our increased capacity to gather and process data. Arguing that the need for statistical sampling is now behind us due to modern computing capacity, the authors discuss how big data's capabilities supersede past methods in applications like tracking the spread of the flu or credit card fraud. Even the human body can be "datafied," with modern applications that use a person's walking gait as a password or monitor body tremors to track the progression of neurological disorders. The rise of big data has helped to create several types of companies: those that own data, those that analyze data, and those that know how to use data to find the answers to new problems. The authors review the risks of this new trend, from privacy concerns to over-reliance on numbers to changes in an individual's responsibility to society. They write with enthusiasm, call for new career paths for algorithmists, and close with a prediction that big data will change the world, from helping solve climate change to improving global health care accessibility. (Mar.) © Copyright PWxyz, LLC. All rights reserved.
Kirkus Review
Plenty of books extol the technical marvels of our information society, but this is an original analysis of the information itself--trillions of searches, calls, clicks, queries and purchases. Mayer-Schnberger (Internet Governance and Regulation/Oxford Univ.; Delete: The Virtue of Forgetting in the Digital Age, 2009) and Economist data editor Cukier begin with a jolt by pointing out that the Centers for Disease Control and Prevention spends weeks evaluating reports from doctors and clinics before announcing a flu epidemic. In a 2009 study reported in the scientific journal Nature, Google engineers tracked certain Internet searches ("medicine for cough," "fever") and detected a rise in flu cases immediately. Formerly, faced with huge numbers, researchers could only examine a select sample: a slow, expensive process that led to errors if the sample wasn't properly chosen. The Google researchers examined everything--or close to everything: hundreds of millions of searches. This was a breakthrough. "Big data," the authors' term for our new ability to manipulate immense amounts of information, reveals not only more, but entirely new knowledge. Who knew that by evaluating her credit card purchases, retailers can calculate the odds that a woman is pregnant? The authors provide an exciting ride without neglecting the risks. Thirty-two surveillance cameras operate within 200 yards of the apartment where George Orwell wrote 1984. Data mining is so efficient that today's privacy protections are irrelevant. Once enough of your activities, however anonymous, are "datafied," a computer can identify you. A fascinating, enthusiastic view of the possibilities of vast computer correlations and the entrepreneurs who are taking advantage of them.]] Copyright Kirkus Reviews, used with permission.
Booklist Review
Academic Mayer-Schonberger and editor Cukier consider big data the new ability to crunch vast collections of information, analyze it instantly, and draw conclusions from it. Big data is about predictions: math applied to large quantities of data in order to infer probabilities. Because big data allows us to analyze far more data, we will move beyond expecting exactness and can no longer be fixated on causation. The authors state, The correlations may not tell us precisely why something is happening, but they alert us that it is happening. For individuals, big data risks an invasion of privacy, as vast amounts of personal data are collected and the potential exists to accuse a person of some possible future behavior that has not happened. The authors conclude that big data is a tool that doesn't offer ultimate answers, just good-enough ones to help us now until better methods and hence better answers come along. This book offers important insights and information for many library patrons.--Whaley, Mary Copyright 2010 Booklist
Choice Review
This work focuses on leveraging large data sets. It would be a useful resource for those studying or researching machine learning, artificial intelligence, algorithms, information systems, and statistics, as well as those within the disciplines of business and medicine. With the availability of inexpensive computer hardware, people can now use and store real-time data sets that were previously disposed of after a single use. Mayer-Schonberger (Oxford Univ., UK) and Cukier (data editor, The Economist) illustrate this through a series of case studies of repurposing data sets for new applications. The authors also outline the social shift in thought from the need to understand why something occurs to accepting that one will not know why it occurs, because the data sets used are too large and time-sensitive. Society is becoming dependent on decisions based on correlation and must accept that there will be outliers in the process. Many books on artificial intelligence focus on the algorithms that drive data sets. Big Data takes a somewhat unique approach in that it focuses on showing how existing and accessible data sets drive algorithm development. Finally, the book outlines the implications of big data for society and personal privacy. Summing Up: Recommended. Upper-division undergraduates through professionals; general readers. S. A. Patton Indiana State University
Table of Contents
| 1 Now | p. 1 |
| 2 More | p. 19 |
| 3 Messy | p. 32 |
| 4 Correlation | p. 50 |
| 5 Datafication | p. 73 |
| 6 Value | p. 98 |
| 7 Implications | p. 123 |
| 8 Risks | p. 150 |
| 9 Control | p. 171 |
| 10 Next | p. 185 |
| Notes | p. 199 |
| Bibliography | p. 217 |
| Acknowledgments | p. 227 |
| Index | p. 231 |