Foreword
Preface
Acknowledgments
Part One The Rise of Big Data
Chapter 1 What Is Big Data and Why Does It Matter?
What Is “Big Data”?
Is the “Big” Part or the “Data” Part More Important?
How Is Big Data Different?
How Is Big Data More of the Same?
Risks of Big Data
Why You Need to Tame Big Data
The Structure of Big Data
Exploring Big Data
Most Big Data Doesn't Matter
Filtering Big Data Effectively
Mixing Big Data with Traditional Data
The Need for Standards
Today's Big Data Is Not Tomorrow's Big Data
Wrap Up
Notes
Chapter 2 Web Data: The Original Big Data
Web Data Overview
What Web Data Reveals
Web Data in Action
Wrap Up
Note
Chapter 3 A Cross-Section of Big Data Sources
Auto Insurance: Telematics Data
Multiple Industries: Text Data
Multiple Industries: Time and Location Data
Retail and Manufacturing: Radio Frequency Identification Data
Utilities: Smart Grid Data
Gaming: Casino Chip Tracking Data
Industrial Engines and Equipment: Sensor Data
Video Games: Telemetry Data
Telecommunications and Other Industries: Social Network Data
Wrap Up
Part Two Taming Big Data: The Technologies, Processes, and Methods
Chapter 4 Evolution of Analytic Scalability
A History of Scalability
Convergence of the Analytic and Data Environments
Massively Parallel Processing Systems
Cloud Computing
Grid Computing
MapReduce
It Isn't an Either / Or Choice!
Wrap Up
Notes
Chapter 5 The Evolution of Analytic Processes
The Analytic Sandbox
What Is an Analytic Data Set?
Enterprise Analytic Data Sets
Embedded Scoring
Wrap Up
Chapter 6 Evolution of Analytic Tools and Methods
Evolution of Analytic Tools
Evolution of Analytic Methods
Wrap-Up
Notes
Part Three Taming Big Data: The People and Approaches
Chapter 7 What Makes a Great Analysis?
Analysis versus Reporting
Analysis: Make It “G.R.E.A.T.”!
“Core” Analytics versus “Advanced” Analytics
Listen to Your Analysis
Framing the Problem Correctly
Statistical Significance versus Business Importance
Samples versus Populations
Making Inferences versus Computing Statistics
Wrap Up
Chapter 8 What Makes a Great Analyst?
The Common Misconceptions
Every Great Analyst Is an Exception
The Often Underrated Traits of a Great Analyst
Is Analytics Certification Needed or Is It Noise?
Wrap Up
Chapter 9 What Makes a Great Analytics Team?
All Industries Are Not Created Equal
Just Get Started!
There's a Talent Crunch Out There
Team Structures
Keeping a Great Team’s Skills Up
Should Non-Analysts Be Doing Advanced Analytics?
Why Can't IT and Analysts Get Along?
Wrap Up
Notes
Part Four Bringing It Together: The Analytics Culture
Chapter 10 Enabling Analytic Innovation
Businesses Need More Innovation
Traditional Approaches Hamper Innovation
Defining Analytic Innovation
Iterative Approaches to Analytic Innovation
Consider a Change in Perspective
Are You Ready for an Analytic Innovation Center?
Wrap Up
Note
Chapter 11 Creating a Culture of Innovation and Discovery
Setting the Stage
Overview of the Key Principles
Wrap Up
Notes
Conclusion: Think Bigger!
About the Author
Index