Prerequisite: This course assumes a basic understanding of dimensional modeling concepts, techniques, and terminology.
When planning and building data marts, your entire team must be fluent in dimensional modeling—not just the data modelers! This course immerses students in the principles, processes, and deliverables of dimensional modeling, equipping you for a successful implementation. You will learn the complete set of best practices—from multiple fact table designs, to bridge tables, to advanced slow change processing. Students learn to match these techniques to real-world business complexity, and explore their impacts on BI and data integration tools. The course explores the reasons behind best practices, and teaches students to make pragmatic decisions when facing design choices.
Students also learn how to fit dimensional modeling into varied development frameworks (including agile), and receive templates for capturing requirements and designs.
You Will Learn
- Why dimensional design requires collaboration between modelers, analysts, DBA’s, and ETL & reporting developers
- Why most subject areas require multiple fact tables, and how to identify them
- When to use alternatives to the basic transaction fact table, including periodic snapshots, accumulating snapshots, and type-specific stars
- How to cope with dimensional intricacy with advanced techniques including bridge tables, minidimensions, and advanced slow change responses
- Techniques to ensure your data warehouse will scale as new subject areas are added
- How design fits into development approaches, and what tasks and outputs should be incorporated
This course is intended for anyone who contributes to data mart development, including:
- BI program & project managers
- Business analysts
- Data modelers and architects
- BI reporting & ETL developers
- “Power users” and business subject matter experts