Data Warehouse Design: Modern Principles and Methodologies - Softcover

Golfarelli, Matteo; Rizzi, Stefano

Softcover

ISBN 10: 0071610391 ISBN 13: 9780071610391

Publisher: McGraw Hill, 2009

Synopsis

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Foreword by Mark Stephen LaRow, Vice President of Products, MicroStrategy

"A unique and authoritative book that blends recent research developments with industry-level practices for researchers, students, and industry practitioners."Il-Yeol Song, Professor, College of Information Science and Technology, Drexel University

About this title

About the Author

Matteo Golfarelli is an associate professor of Computer Science and Technology at the University of Bologna, Italy, where he teaches courses in information systems, databases, and data mining.

Stefano Rizzi is a full professor of Computer Science and Technology at the University of Bologna, Italy, where he teaches courses in advanced information systems and software engineering.

From the Back Cover

Plan, Design, and Document High-Performance Data Warehouses

Set up a reliable, secure decision-support infrastructure using the cuttingedge techniques contained in this comprehensive volume. Data Warehouse Design: Modern Principles and Methodologies presents a practical design approach based on solid software engineering principles. Find out how to interview end users, construct expressive conceptual schemata and translate them into relational schemata, and design state-of-the-art ETL procedures. You will also learn how to integrate heterogeneous data sources, implement star and snowflake schemata, manage dynamic and irregular hierarchies, and fine-tune performance by materializing and fragmenting views.

• Work with data- and requirement-driven methodological approaches
• Create a reconciled database to boost data mart architecture
• Capture and expressively represent end-user requirements
• Build a conceptual data mart schema using the Dimensional Fact Model
• Estimate data mart volume and workload
• Improve performance using advanced logical modeling techniques
• Extract, transform, cleanse, and load data from operational sources
• Use sophisticated indexing techniques to optimize query execution plans
• Comprehensively document data warehouse projects
• Discover innovative business intelligence techniques

Edition details

• Publisher: McGraw Hill
• Publication date: 2009
• Language: English
• ISBN 10: 0071610391
• ISBN 13: 9780071610391
• Binding: Paperback
• Edition number: 1
• Number of pages: 480