Too Big to Ignore
The Business Case for Big Data
SAS Institute Inc
1. Edition December 2015
256 Pages, Softcover
Wiley & Sons Ltd
Residents in Boston, Massachusetts are automatically reporting potholes and road hazards via their smartphones. Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior.
How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions.
It's time to start thinking big.
In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate.
Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.
Preface xvii
Acknowledgments xxiii
Introduction This Ain't Your Father's Data 1
Better Car Insurance through Data 2
Potholes and General Road Hazards 5
Recruiting and Retention 8
How Big is Big? The Size of Big Data 10
Why Now? Explaining the Big Data Revolution 12
Central Thesis of Book 22
Plan of Attack 24
Who Should Read This Book? 25
Summary 25
Notes 26
Chapter 1 Data 101 and the Data Deluge 29
The Beginnings: Structured Data 30
Structure This! Web 2.0 and the Arrival of Big Data 33
The Composition of Data: Then and Now 39
The Current State of the Data Union 41
The Enterprise and the Brave New Big Data World 43
Summary 46
Notes 47
Chapter 2 Demystifying Big Data 49
Characteristics of Big Data 50
The Anti-Definition: What Big Data Is Not 71
Summary 72
Notes 72
Chapter 3 The Elements of Persuasion: Big Data Techniques 77
The Big Overview 79
Statistical Techniques and Methods 80
Data Visualization 84
Automation 88
Semantics 93
Big Data and the Gang of Four 98
Predictive Analytics 100
Limitations of Big Data 105
Summary 106
Notes 107
Chapter 4 Big Data Solutions 111
Projects, Applications, and Platforms 114
Other Data Storage Solutions 121
Websites, Start-ups, and Web Services 128
Hardware Considerations 133
The Art and Science of Predictive Analytics 136
Summary 137
Notes 137
Chapter 5 Case Studies: The Big Rewards of Big Data 141
Quantcast: A Small Big Data Company 141
Explorys: The Human Case for Big Data 147
NASA: How Contests, Gamification, and Open Innovation
Enable Big Data 152
Summary 158
Notes 158
Chapter 6 Taking the Big Plunge 161
Before Starting 161
Starting the Journey 165
Avoiding the Big Pitfalls 174
Summary 181
Notes 181
Chapter 7 Big Data: Big Issues and Big Problems 183
Privacy: Big Data = Big Brother? 184
Big Security Concerns 188
Big, Pragmatic Issues 189
Summary 195
Notes 196
Chapter 8 Looking Forward: The Future of Big Data 197
Predicting Pregnancy 198
Big Data Is Here to Stay 200
Big Data Will Evolve 201
Projects and Movements 203
Big Data Will Only Get Bigger...and Smarter 205
The Internet of Things: The Move from Active to Passive Data
Generation 206
Big Data: No Longer a Big Luxury 211
Stasis Is Not an Option 212
Summary 213
Notes 214
Final Thoughts 217
Spreading the Big Data Gospel 219
Notes 220
Selected Bibliography 221
About the Author 223
Index 225
