Taming The Big Data Tidal Wave Finding Opportunities in Huge Data Streams with Advanced Analytics

by Franks, Bill; Davenport, Thomas H.

• ISBN13: 9781118208786
• ISBN10: 1118208781
• eBook ISBN(s): 9781118241172
• Edition: 1st
• Format: Hardcover
• Copyright: 2012-04-24
• Publisher: Wiley
• More Book Details

Summary

Written in an informal style, by someone who has lived analytics in big business, this provides a "from the trenches" viewpoint of analytics. This book shows how Big Data is changing the world of analytics; what people, processes, and mindsets are necessary to succeed in analytics; what trends are developing that will change how businesses do analytics as Big Data alters the scale of the inputs and growing requirements change the scale of the outputs; how to think bigger in terms of what analytics can do for a business; how analytics has evolved in the past decades and how it will continue to evolve in the coming decades; some of the key changes within the tools and technologies used for analytics and how they've changed the game already, with more to come; and what leading companies are doing to ensure innovation in analytics is occurring within their organizations.

Author Biography

Bill Franks is Chief Analytics Officer for Teradata's global alliance programs. Bill also oversees the Business Analytics Innovation Center, which is jointly sponsored by Teradata and SAS and focuses on helping clients pursue innovative analytics. In addition, Bill is a faculty member of the International Institute for Analytics and is an active speaker and blogger. His analytic consulting work has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations.

Table of Contents

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