Big Data

A Revolution That Will Transform How We Live, Work, and Think

Viktor Mayer-Schönberger, Kenneth Cukier

• Publisher: Harper Business
• Year: 2013
• Print ISBN: 9780544227750
• eBook ISBN: 9780544002937
• Topic: Business
• Subtopic: Business General
• Index: Business

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

Index

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

A

abacuses, 80

Accenture, 128, 131

accountability, individual: big data and, 177–78, 193

Acxiom, 100, 150

airlines

Etzioni analyzes fare pricing patterns, 3–5, 11, 14, 27, 55, 76, 103, 126, 191

flight delay predictions, 117–18, 129–30

AirSage, 90, 106

“algorithmists,” 180–82

algorithms, computer, 7–8, 60

improvements in, 35–37

transparency of, 179

Alta Vista, 112

Amazon, 12, 14, 101, 115, 131, 147, 151

as big-data company, 132

book reviews at, 50–51, 141

collaborative filtering at, 51–52, 132

data-reuse by, 105, 110

and e-books, 85–86

Amazonia (Marcus), 51

ancient world: record-keeping in, 20–21

Anderson, Chris: on “end of theory,” 70–72

anonymization: big data defeats, 155–56, 192

of data, 152, 154–55

privacy and, 154–56

antitrust regulation: big data and, 182–84

AOL: fails to understand data-reuse, 105

releases personal data, 154–55

Apple, 95, 168

and cell phone data, 146

Arabic numerals, 80–82

Arnold, Thelma, 154–55

artificial intelligence: big data and, 11–12

at Google, 10

Asthmapolis, 95

astronomy: big data in, 7

automobiles: anti-theft systems, 77

data-gathering by, 133–34, 137–38, 149, 156, 173–74

automobiles, electric: big data and, 102–103

IBM and, 102–103

automobiles, self-driving, 12, 109, 132, 191

Aviva, 56–57

Ayres, Ian: Super Crunchers, 141

B

Bacon, Francis, 33

Banko, Michele, 36, 39

Barabási, Albert-László, 30–31

Barnes & Noble, 114–15

Basis, 95

Beane, Billy, 140–41

Being Digital (Negroponte), 78

Bell Labs, 167

Berners-Lee, Tim, 117

Bezos, Jeff, 5...

Table of contents

• Title Page
• Contents
• Copyright
• Dedication
• Now
• More
• Messy
• Correlation
• Datafication
• Value
• Implications
• Risks
• Control
• Next
• Afterword
• Notes
• Bibliography
• Acknowledgments
• Index
• About the Authors
• Connect with HMH