Agile Data Warehousing Project Management

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Informationen zum Autor 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. Klappentext Data warehousing involves making sense out of enormous amounts of data, and for most warehousing professionals the notion of agile data warehousing sounds risky but compelling. Agile data warehousing techniques yield as much as a 3:1 speed advantage while cutting project costs in half. Agile Data Warehousing Project Management aims to bring this crazy-sounding yet highly effective technique to the masses by providing a thorough introduction to the method as one would practice it in the project room to build a serious data mart. This step-by-step presentation will bring the novice to the point where they can join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse. Zusammenfassung Offers an introduction to the method as you would practice it in the project room to build a data mart. This title helps to prepare you to join or lead a team in visualizing! building! and validating a single component to an enterprise data warehouse. It includes strategies for getting actionable requirements from a team's business partner. Inhaltsverzeichnis Part I: A Generic Agile Method Chapter 1. Why Agile?Chapter 2. Agile Development in a NutshellChapter 3. Project Management LiteChapter 4. User Stories for Business Intelligence Applications Part II. Adapting Agile to Data Warehousing Chapter 5. Developer Stories for Data Integration ProjectsChapter 6. Agile Estimation for DW/BIChapter 7. Further Adaptations for Agile Data WarehousingChapter 8. Starting and Scaling Agile Warehousing Teams Part III. Retrospective Chapter 9. Faster, Better, Cheaper ...

Autorentext
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.

Klappentext
Data warehousing involves making sense out of enormous amounts of data, and for most warehousing professionals the notion of agile data warehousing sounds risky but compelling. Agile data warehousing techniques yield as much as a 3:1 speed advantage while cutting project costs in half. Agile Data Warehousing Project Management aims to bring this crazy-sounding yet highly effective technique to the masses by providing a thorough introduction to the method as one would practice it in the project room to build a serious data mart. This step-by-step presentation will bring the novice to the point where they can join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse.


Zusammenfassung
Offers an introduction to the method as you would practice it in the project room to build a data mart. This title helps to prepare you to join or lead a team in visualizing, building, and validating a single component to an enterprise data warehouse. It includes strategies for getting actionable requirements from a team's business partner.

Inhalt

Part I: A Generic Agile MethodChapter 1. Why Agile?Chapter 2. Agile Development in a NutshellChapter 3. Project Management LiteChapter 4. User Stories for Business Intelligence Applications

Part II. Adapting Agile to Data WarehousingChapter 5. Developer Stories for Data Integration ProjectsChapter 6. Agile Estimation for DW/BIChapter 7. Further Adaptations for Agile Data WarehousingChapter 8. Starting and Scaling Agile Warehousing Teams

Part III. RetrospectiveChapter 9. Faster, Better, Cheaper

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09780123964632
    • Sprache Englisch
    • Größe H235mm x B191mm x T19mm
    • Jahr 2012
    • EAN 9780123964632
    • Format Kartonierter Einband
    • ISBN 978-0-12-396463-2
    • Veröffentlichung 10.12.2012
    • Titel Agile Data Warehousing Project Management
    • Autor Hughes Ralph
    • Untertitel Business Intelligence Systems Using Scrum
    • Gewicht 770g
    • Herausgeber Elsevier LTD, Oxford
    • Anzahl Seiten 366
    • Genre Informatik

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