Реклама. ООО «ЛитРес», ИНН: 7719571260.
Introduction
Overview of the Book and Technology
How This Book Is Organized
Who Should Read This Book
Tools You Will Need
What's on the Website
What This Means for You
Part I. Business Potential of Big Data
Chapter 1. The Big Data Business Mandate
Big Data MBA Introduction
Focus Big Data on Driving Competitive Differentiation
Critical Importance of “Thinking Differently”
Summary
Homework Assignment
Chapter 2. Big Data Business Model Maturity Index
Introducing the Big Data Business Model Maturity Index
Big Data Business Model Maturity Index Lessons Learned
Summary
Homework Assignment
Chapter 3. The Big Data Strategy Document
Establishing Common Business Terminology
Introducing the Big Data Strategy Document
Introducing the Prioritization Matrix
Using the Big Data Strategy Document to Win the World Series
Summary
Homework Assignment
Chapter 4. The Importance of the User Experience
The Unintelligent User Experience
Consumer Case Study: Improve Customer Engagement
Business Case Study: Enable Frontline Employees
B2B Case Study: Make the Channel More Effective
Summary
Homework Assignment
Part II. Data Science
Chapter 5. Differences Between Business Intelligence and Data Science
What Is Data Science?
The Analyst Characteristics Are Different
The Analytic Approaches Are Different
The Data Models Are Different
The View of the Business Is Different
Summary
Homework Assignment
Chapter 6. Data Science 101
Data Science Case Study Setup
Fundamental Exploratory Analytics
Analytic Algorithms and Models
Summary
Homework Assignment
Chapter 7. The Data Lake
Introduction to the Data Lake
Characteristics of a Business-Ready Data Lake
Using the Data Lake to Cross the Analytics Chasm
Modernize Your Data and Analytics Environment
Analytics Hub and Spoke Analytics Architecture
Early Learnings
What Does the Future Hold?
Summary
Homework Assignment
Part III. Data Science for Business Stakeholders
Chapter 8. Thinking Like a Data Scientist
The Process of Thinking Like a Data Scientist
Summary
Homework Assignment
Chapter 9 “By” Analysis Technique
“By” Analysis Introduction
“By” Analysis Exercise
Foot Locker Use Case “By” Analysis
Summary
Homework Assignment
Chapter 10. Score Development Technique
Definition of a Score
FICO Score Example
Other Industry Score Examples
LeBron James Exercise Continued
Foot Locker Example Continued
Summary
Homework Assignment
Chapter 11. Monetization Exercise
Fitness Tracker Monetization Example
Summary
Homework Assignment
Chapter 12. Metamorphosis Exercise
Business Metamorphosis Review
Business Metamorphosis Exercise
Business Metamorphosis in Health Care
Summary
Homework Assignment
Part IV. Building Cross-Organizational Support
Chapter 13. Power of Envisioning
Envisioning: Fueling Creative Thinking
The Prioritization Matrix
Summary
Homework Assignment
Chapter 14. Organizational Ramifications
Chief Data Monetization Officer
Privacy, Trust, and Decision Governance
Unleashing Organizational Creativity
Summary
Homework Assignment
Chapter 15. Stories
Customer and Employee Analytics
Product and Device Analytics
Network and Operational Analytics
Characteristics of a Good Business Story
Summary
Homework Assignment
About the Author
About the Technical Editor
Credits
Acknowledgments
WILEY END USER LICENSE AGREEMENT
I never planned on writing a second book. Heck, I thought writing one book was enough to check this item off my bucket list. But so much has changed since I wrote my first book that I felt compelled to continue to explore this once-in-a-lifetime opportunity for organizations to leverage data and analytics to transform their business models. And I'm not just talking the “make me more money” part of businesses. Big data can drive significant “improve the quality of life” value in areas such as education, poverty, parole rehabilitation, health care, safety, and crime reduction.
My first book targeted the Information Technology (IT) audience. However, I soon realized that the biggest winner in this big data land grab was the business. So this book targets the business audience and is based on a few key premises:
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More than anything else, the driving force behind big data is the economics of big data – it's 20 to 50 times cheaper to store, manage, and analyze data than it is to use traditional data warehousing technologies. This 20 to 50 times economic impact is courtesy of commodity hardware, open source software, an explosion of new open source tools coming out of academia, and ready access to free online training on topics such as big data architectures and data science. A client of mine in the insurance industry calculated a 50X economic impact. Another client in the health care industry calculated a 49X economic impact (they need to look harder to find that missing 1X).
History has shown that the most significant technology innovations are ones that drive economic change. From the printing press to interchangeable parts to the microprocessor, these technology innovations have provided an unprecedented opportunity for the more agile and more nimble organizations to disrupt existing markets and establish new value creation processes.
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