Agile Data Warehousing Project Management: Business Intelligence Systems Using Scrum

You have to make sense of enormous amounts of data, and while the notion of "agile data warehousing” might sound tricky, it can yield as much as a 3-to-1 speed advantage while cutting project costs in half. Bring this highly effective technique to your organization with the wisdom of agile data warehousing expert Ralph Hughes. Agile Data Warehousing Project Management will give you a thorough introduction to the method as you would practice it in the project room to build a serious "data mart.” Regardless of where you are today, this step-by-step implementation guide will prepare you to join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse.

• Provides a thorough grounding on the mechanics of Scrum as well as practical advice on keeping your team on track
• Includes strategies for getting accurate and actionable requirements from a team's business partner
• Revolutionary estimating techniques that make forecasting labor far more understandable and accurate
• Demonstrates a blends of Agile methods to simplify team management and synchronize inputs across IT specialties
• Enables you and your teams to start simple and progress steadily to world-class performance levels

About the Author

Ralph Hughes, former DW/BI practice manager for a leading global systems integrator, has led numerous BI programs and projects for Fortune 500 companies in aerospace, government, telecom, and pharmaceuticals.

A certified Scrum Master and a PMI Project Management Professional, he began developing an agile method for data warehouse 15 years ago, and was the first to publish books on the iterative solutions for business intelligence projects.

He is a veteran trainer with the world's leading data warehouse institute and has instructed or coached over 1,000 BI professionals worldwide in the discipline of incremental delivery of large data management systems.

A frequent keynote speaker at business intelligence and data management events, he serves as a judge on emerging technologies award panels and program advisory committees of advanced technology conferences.

He holds BA and MA degrees from Stanford University where he studied computer modeling and econometric forecasting.

A co-inventor of Zuzena, the automated testing engine for data warehouses, he serves as Chief Systems Architect for Ceregenics and consults on agile projects internationally.