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Leaders and Innovators

Book Description

An integrated, strategic approach to higher-value analytics

Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows how businesses leverage enterprise analytics to gain strategic insights for profitability and growth. The key factor is integrated, end-to-end capabilities that encompass data management and analytics from a business and IT perspective; with analytics running inside a database where the data reside, everyday analytical processes become streamlined and more efficient. This book shows you what analytics is, what it can do, and how you can integrate old and new technologies to get more out of your data. Case studies and examples illustrate real-world scenarios in which an optimized analytics system revolutionized an organization's business. Using in-database and in-memory analytics along with Hadoop, you'll be equipped to improve performance while reducing processing time from days or weeks to hours or minutes. This more strategic approach uncovers the opportunities hidden in your data, and the detailed guidance to optimal data management allows you to break through even the biggest data challenges.

With data coming in from every angle in a constant stream, there has never been a greater need for proactive and agile strategies to overcome these struggles in a volatile and competitive economy. This book provides clear guidance and an integrated strategy for organizations seeking greater value from their data and becoming leaders and innovators in the industry.

  • Streamline analytics processes and daily tasks
  • Integrate traditional tools with new and modern technologies
  • Evolve from tactical to strategic behavior
  • Explore new analytics methods and applications

The depth and breadth of analytics capabilities, technologies, and potential makes it a bottomless well of insight. But too many organizations falter at implementation—too much, not enough, or the right amount in the wrong way all fail to deliver what an optimized and integrated system could. Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows you how to create the system your organization needs to dramatically improve performance, increase profitability, and drive innovation at all levels for the present and future.

Table of Contents

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