Bill Franks 
Taming The Big Data Tidal Wave [PDF ebook] 
Finding Opportunities in Huge Data Streams with Advanced Analytics

You receive an e-mail. It contains an offer for a complete personal
computer system. It seems like the retailer read your mind since
you were exploring computers on their web site just a few hours
prior….

As you drive to the store to buy the computer bundle, you get an
offer for a discounted coffee from the coffee shop you are getting
ready to drive past. It says that since you’re in the area,
you can get 10% off if you stop by in the next 20
minutes….

As you drink your coffee, you receive an apology from the
manufacturer of a product that you complained about yesterday on
your Facebook page, as well as on the company’s web
site….

Finally, once you get back home, you receive notice of a special
armor upgrade available for purchase in your favorite online video
game. It is just what is needed to get past some spots
you’ve been struggling with….

Sound crazy? Are these things that can only happen in the
distant future? No. All of these scenarios are possible today! Big
data. Advanced analytics. Big data analytics. It seems you
can’t escape such terms today. Everywhere you turn people are
discussing, writing about, and promoting big data and advanced
analytics. Well, you can now add this book to the discussion.

What is real and what is hype? Such attention can lead one to
the suspicion that perhaps the analysis of big data is something
that is more hype than substance. While there has been a lot of
hype over the past few years, the reality is that we are in a
transformative era in terms of analytic capabilities and the
leveraging of massive amounts of data. If you take the time to cut
through the sometimes-over-zealous hype present in the media,
you’ll find something very real and very powerful underneath
it. With big data, the hype is driven by genuine excitement and
anticipation of the business and consumer benefits that analyzing
it will yield over time.

Big data is the next wave of new data sources that will drive
the next wave of analytic innovation in business, government, and
academia. These innovations have the potential to radically change
how organizations view their business. The analysis that big data
enables will lead to decisions that are more informed and, in some
cases, different from what they are today. It will yield insights
that many can only dream about today. As you’ll see, there
are many consistencies with the requirements to tame big data and
what has always been needed to tame new data sources. However, the
additional scale of big data necessitates utilizing the newest
tools, technologies, methods, and processes. The old way of
approaching analysis just won’t work. It is time to evolve
the world of advanced analytics to the next level. That’s
what this book is about.

Taming the Big Data Tidal Wave isn’t just the title
of this book, but rather an activity that will determine which
businesses win and which lose in the next decade. By preparing and
taking the initiative, organizations can ride the big data tidal
wave to success rather than being pummeled underneath the crushing
surf. What do you need to know and how do you prepare in order to
start taming big data and generating exciting new analytics from
it? Sit back, get comfortable, and prepare to find out!

İçerik tablosu

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

Map Reduce

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

Yazar hakkında

BILL FRANKS is the Chief Analytics Officer for Teradata, where he provides insight on trends in the analytics and big data space and helps organizations implement their analytics effectively. In addition, Bill is a faculty member of the International Institute for Analytics and is an active speaker and blogger. His consulting work has spanned many industries for companies ranging from Fortune 100 companies to small non-profits.