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.