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by Bill Franks, James Taylor, Tho H. Nguyen
Leaders and Innovators
Foreword
Acknowledgments
About the Author
Introduction
Why You Should Read This Book
Let's Start with Definitions
Industry Trends and Challenges
Who Should Read This Book?
How to Read This Book
Let Your Journey Begin
Endnotes
Chapter 1: The Analytical Data Life Cycle
Stage 1: Data Exploration
Stage 2: Data Preparation
Stage 3: Model Development
Stage 4: Model Deployment
End-to-End Process
Chapter 2: In-Database Processing
Background
Traditional Approach
In-Database Approach
The Need for In-Database Analytics
Success Stories and Use Cases
In-Database Data Quality
Investment for In-Database Processing
Endnotes
Chapter 3: In-Memory Analytics
Background
Traditional Approach
In-Memory Analytics Approach
The Need for In-Memory Analytics
Success Stories and Use Cases
Investment for In-Memory Analytics
Chapter 4: Hadoop
Background
Hadoop in the Big Data Environment
Use Cases for Hadoop
Hadoop Architecture
Best Practices
Benefits of Hadoop
Use Cases and Success Stories
A Collection of Use Cases
Endnote
Chapter 5: Bringing It All Together
Background
Collaborative Data Architecture
Scenarios for the Collaborative Data Architecture
How In-Database, In-Memory, and Hadoop Are Complementary in a Collaborative Data Architecture
Use Cases and Customer Success Stories
Investment and Costs
Endnotes
Chapter 6: Final Thoughts and Conclusion
Five Focus Areas
Cloud Computing
Security: Cyber, Data Breach
Automating Prescriptive Analytics: Iot, Events, and Data Streams
Cognitive Analytics
Anything as a Service (XaaS)
Conclusion
Afterword
Index
End User License Agreement
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Leaders and Innovators
How Data-Driven Organizations Are Winning with Analytics
Tho H. Nguyen
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