Skip to main content

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


CAD $59.95

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

Bill Franks, Thomas H. Davenport (Foreword by)

ISBN: 978-1-118-20878-6 April 2012 336 Pages

Download Product Flyer

Download Product Flyer

Download Product Flyer is to download PDF in new tab. This is a dummy description. Download Product Flyer is to download PDF in new tab. This is a dummy description. Download Product Flyer is to download PDF in new tab. This is a dummy description. Download Product Flyer is to download PDF in new tab. This is a dummy description.


Finding Opportunities in Huge Data Streams with Advanced Analytics

"This book . . . puts the focus squarely where it belongs . . . It's primarily about the effective analysis of big data, rather than the big data management (BDM) topic per se. It starts with data and goes all the way into such topics as how to frame decisions, how to build an analytics center of excellence, and how to build an analytical culture. You will find some mentions of BDM topics, as you should. But the bulk of the content here is about how to create, organize, staff, and execute on analytical initiatives that make use of data as the input."
—From the Foreword by Thomas H. Davenport, President's Distinguished Professor of IT and Management, Babson College, cofounder and Research Director, International Institute for Analytics

"This is a one-stop handbook for anyone who wants to understand what big data is and how to leverage it through advanced analytic processes and methods. Bill Franks intimately understands and describes how to create an entire analytics ecosystem intended to deliver competitive advantage."
—Stuart Aitken, CEO, dunnhumby USA

"In Taming the Big Data Tidal Wave, Bill Franks does a great job introducing both big data and the kind of analytics that will generate value from the waves of new data that are washing over companies. Easy to read and with helpful wrap-up sections in each chapter, the book avoids technical jargon without being lightweight. In this great introductory book, Bill makes a powerful case for analytic innovation and for getting started now."
—James Taylor, CEO, Decision Management Solutions and author of Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics

"In case you ever wondered why big data is providing business value in many industries, this book gives you perspectives and answers from many angles—from the tech side, to data science, to business users and processes. In my entire career of researching and lecturing on analytics, I have never encountered a book that combines the knowledge of both information technology and business managers in such a succinct way. I would recommend it to anyone whose career intersects with big data."
—Diego Klabjan, Professor at Northwestern University; Director, Master of Science in Analytics

"Bill Franks provides an entertaining and consumable take on a complex and intricate topic. The mix of insights applicable to practitioners and novices alike make this a critical read for someone new to the analytics space or to anyone in the space wanting to ensure they can learn from an accomplished leader. Franks' view across multiple industries and uses of big data have positioned him well to deliver this entry into the emergence of the space."
—Richard Maltsbarger, Senior Vice President of Strategy, Lowe's Companies, Inc.

Foreword xiii

Preface xvii

Acknowledgments xxv


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


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


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


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