Table of Contents

The Chess Pieces. PROJECT MANAGEMENT AND REQUIREMENTS. The Business Dimensional Lifecycle. Project Planning and Management. Collecting the Requirements. DATA DESIGN. A First Course on Dimensional Modeling. A Graduate Course on Dimensional Modeling. Building Dimensional Models. ARCHITECTURE. Introducing Data Warehouse Architecture. Back Room Technical Architecture. Architecture for the Front Room. Infrastructure and Metadata. A Graduate Course on the Internet and Security. Creating the Architecture Plan and Selecting Products. IMPLEMENTATION. A Graduate Course on Aggregates. Completing the Physical Design. Data Staging. Building End User Applications. DEPLOYMENT AND GROWTH. Planning the Deployment. Maintaining and Growing the Data Warehouse. Appendices. Index.

About the Author

RALPH KIMBALL has been a leading visionary in the data warehouse industry since 1982 and is one of today's most internationally well--known speakers, consultants, and teachers on data warehousing. He writes the "Data Warehouse Architect" column for Intelligent Enterprise (formerly DBMS) magazine. Dr. Kimball's coauthors have each founded their own very successful data warehouse consulting firms: Laura Reeves of StarSoft Solutions; Margy Ross of DecisionWorks Consulting; and Warren Thornthwaite of InfoDynamics LLC.

Reviews

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Das Buch richtet sich primdr an Designer und Informations-Manager im Umfeld von Data-Warehouse-Anwendungen. Diese Zielgruppe erhdlt Ratschldge und Handlungsanleitungen, um deren Anforderungen optimal zu bewdltigen. Dabei ist der ganzheitliche Ansatz zu betonen, der eine evolutiondre Weiterentwicklung besser als singuldre Schnellsch]sse unterst]tzen kann. auch der zugrundeliegende Architekturcharakter trdgt zur Festigung dieser Intension bei. Zu knapp werden die Themen Data Mining und Parallelverarbeitung angesprochen; ebenfalls fehlen zur Vertiefung weiterf]hrende Literaturhinweise. Insbesondere SMP und MPP bieten f]r die praktische Realisierung wichtige Unterst]tzungshilfen. Wobei zur Verbesserung der Performance die Fdhigkeit einiger DBMS Abfragen zu optimieren und parallel zu verarbeiten n]tzlich ist.
IT-Director 10/2000