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Book Description

Using Agile methods, you can bring far greater innovation, value, and quality to any data warehouse, business intelligence, or analytics project. However, conventional Agile methodologies must be carefully adapted to address the unique characteristics of DW/BI projects. In Agile Analytics, Agile pioneer Ken Collier shows how to do just that.

Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets; support enormous and fast-growing data volumes; and more. Collier's techniques offer equal value whether your projects involve "back-end" data management, "front-end" business analysis, or both.

  • Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your agile DW/BI project community works together towards success

  • Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation

Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, DBA, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way.

Table of Contents

  1. Title Page
  2. Praise for Agile Analytics
  3. Copyright Page
  4. Dedication
  5. Contents
  6. Foreword by Jim Highsmith
  7. Foreword by Wayne Eckerson
  8. Preface
  9. Acknowledgments
  10. About the Author
  11. Part I. Agile Analytics: Management Methods
    1. Chapter 1. Introducing Agile Analytics
    2. Chapter 2. Agile Project Management
    3. Chapter 3. Community, Customers, and Collaboration
    4. Chapter 4. User Stories for BI Systems
    5. Chapter 5. Self-Organizing Teams Boost Performance
  12. Part II. Agile Analytics: Technical Methods
    1. Chapter 6. Evolving Excellent Design
    2. Chapter 7. Test-Driven Data Warehouse Development
    3. Chapter 8. Version Control for Data Warehousing
    4. Chapter 9. Project Automation
    5. Chapter 10. Final Words
  13. References and Recommended Reading
  14. Index
  15. Footnotes
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