We specialize in hard to find items
All Categories
Data Warehouse Design: Modern Principles and Methodologies
Share Tweet
*Price and Stocks may change without prior notice
*Packaging of actual item may differ from photo shown
- Electrical items MAY be 110 volts.
- 7 Day Return Policy
- All products are genuine and original
About Data Warehouse Design: Modern Principles And
Product Description Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. 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 Publisher 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 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.
