- eBook:Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing
- Author:Ken Collier
- Edition:1 edition
- Data:July 27, 2011
- Pages:368 pages
- Format:PDF, ePUB
Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods 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 and how to support enormous and fast-growing data volumes. Collier’s techniques offer optimal 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 can collaborate toward 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, database administrator, 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.
Chapter 1. Introducing Agile Analytics
Chapter 2. Agile Project Management
Chapter 3. Community, Customers, and Collaboration
Chapter 4. User Stories for BI Systems
Chapter 5. Self-Organizing Teams Boost Performance
Part II - Agile Analytics: Technical Methods
Chapter 6. Evolving Excellent Design
Chapter 7. Test-Driven Data Warehouse Development
Chapter 8. Version Control for Data Warehousing
Chapter 9. Project Automation
Chapter 10. Final Words