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.
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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
PHIL SIMON is a frequent keynote speaker, a recognized technology authority, and the award-winning author of seven management books. His contributions have been featured in The Harvard Business Review, Wired, BusinessWeek, The Huffington Post, and The New York Times, and on CNN, NBC, and CNBC.
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List of Tables and Figures xv 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
List of Tables and Figures xv 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
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