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Data Warehouse Design: Modern Principles and Methodologies

Matteo Golfarelli; Stefano Rizzi

18 ratings by Goodreads
ISBN 10: 0071610391 / ISBN 13: 9780071610391
Published by McGraw-Hill Osborne Media, 2009
Used Condition: Used: Good Soft cover
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Bibliographic Details

Title: Data Warehouse Design: Modern Principles and...

Publisher: McGraw-Hill Osborne Media

Publication Date: 2009

Binding: Paperback

Book Condition: Used: Good

About this title


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

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

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