Taming The Big Data Tidal Wave

Foreword xiii Preface xvii Acknowledgments xxv PART ONE THE RISE OF BIG DATA 1 Chapter 1 What Is Big Data and Why Does It Matter? 3 What Is Big Data? 4 Is the "Big" Part or the "Data" Part More Important? 5 How Is Big Data Different? 7 How Is Big Data More of the Same? 9 Risks of Big Data 10 Why You Need to Tame Big Data 12 The Structure of Big Data 14 Exploring Big Data 16 Most Big Data Doesn't Matter 17 Filtering Big Data Effectively 20 Mixing Big Data with Traditional Data 21 The Need for Standards 22 Today's Big Data Is Not Tomorrow's Big Data 24 Wrap-Up 26 Notes 27 Chapter 2 Web Data: The Original Big Data 29 Web Data Overview 30 What Web Data Reveals 36 Web Data in Action 42 Wrap-Up 50 Note 51 Chapter 3 A Cross-Section of Big Data Sources and the Value They Hold 53 Auto Insurance: The Value of Telematics Data 54 Multiple Industries: The Value of Text Data 57 Multiple Industries: The Value of Time and Location Data 60 Retail and Manufacturing: The Value of Radio Frequency Identification Data 64 Utilities: The Value of Smart-Grid Data 68 Gaming: The Value of Casino Chip Tracking Data 71 Industrial Engines and Equipment: The Value of Sensor Data 73 Video Games: The Value of Telemetry Data 76 Telecommunications and Other Industries: The Value of Social Network Data 78 Wrap-Up 82 PART TWO TAMING BIG DATA: THE TECHNOLOGIES, PROCESSES, AND METHODS 85 Chapter 4 The Evolution of Analytic Scalability 87 A History of Scalability 88 The Convergence of the Analytic and Data Environments 90 Massively Parallel Processing Systems 93 Cloud Computing 102 Grid Computing 109 MapReduce 110 It Isn't an Either/Or Choice! 117 Wrap-Up 118 Notes 119 Chapter 5 The Evolution of Analytic Processes 121 The Analytic Sandbox 122 What Is an Analytic Data Set? 133 Enterprise Analytic Data Sets 137 Embedded Scoring 145 Wrap-Up 151 Chapter 6 The Evolution of Analytic Tools and Methods 153 The Evolution of Analytic Methods 154 The Evolution of Analytic Tools 163 Wrap-Up 175 Notes 176 PART THREE TAMING BIG DATA: THE PEOPLE AND APPROACHES 177 Chapter 7 What Makes a Great Analysis? 179 Analysis versus Reporting 179 Analysis: Make It G.R.E.A.T.! 184 Core Analytics versus Advanced Analytics 186 Listen to Your Analysis 188 Framing the Problem Correctly 189 Statistical Signifi cance versus Business Importance 191 Samples versus Populations 195 Making Inferences versus Computing Statistics 198 Wrap-Up 200 Chapter 8 What Makes a Great Analytic Professional? 201 Who Is the Analytic Professional? 202 The Common Misconceptions about Analytic Professionals 203 Every Great Analytic Professional Is an Exception 204 The Often Underrated Traits of a Great Analytic Professional 208 Is Analytics Certifi cation Needed, or Is It Noise? 222 Wrap-Up 224 Chapter 9 What Makes a Great Analytics Team? 227 All Industries Are Not Created Equal 228 Just Get Started! 230 There's a Talent Crunch out There 231 Team Structures 232 Keeping a Great Team's Skills Up 237 Who Should Be Doing Advanced Analytics? 241 Why Can't IT and Analytic Professionals Get Along? 245 Wrap-Up 247 Notes 248 PART FOUR BRINGING IT TOGETHER: THE ANALYTICS CULTURE 249 Chapter 10 Enabling Analytic Innovation 251 Businesses Need More Innovation 252 Traditional Approaches Hamper Innovation 253 Defi ning Analytic Innovation 255 Iterative Approaches to Analytic Innovation 256 Consider a Change in Perspective 257 Are You Ready for an Analytic Innovation Center? 259 Wrap-Up 269 Note 270 Chapter 11 Creating a Culture of Innovation and Discovery 271 Setting the Stage 272 Overview of the Key Principles 274 Wrap-Up 290 Notes 291 Conclusion: Think Bigger! 293 About the Author 295 Index 297