Data Warehouse Design: Modern Principles and Methodologies

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