Buch, Englisch, 336 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 638 g
Reihe: SAS Institute Inc
Buch, Englisch, 336 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 638 g
Reihe: SAS Institute Inc
ISBN: 978-1-118-20878-6
Verlag: Wiley
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!
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Medien-, Informations und Kommunikationswirtschaft Informationstechnik, IT-Industrie
- Wirtschaftswissenschaften Wirtschaftswissenschaften Literatur für Manager
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management E-Commerce, E-Business, E-Marketing
- Wirtschaftswissenschaften Wirtschaftswissenschaften Wirtschaft: Sachbuch, Ratgeber
Weitere Infos & Material
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