This Dimensional Data Modeling training course provides skills on dimensional modeling principles, processes, and deliverables. Starting from the basics, learn a complete set of best practices—from multiple fact table designs, to bridge tables, to advanced slow change processing.
By attending Dimensional Data Modeling workshop, delegates will learn:
- How to capture actionable business requirements
- How to build a logical dimensional data model
- How to translate a logical dimensional model into a star-schema design
- 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 using techniques such as bridge tables, mini-dimensions, time-stamped dimensions, hybrid slow changes, and other slow change options
- Techniques to ensure your data warehouse will scale as new subject areas are added
- How design fits into development methods, who should be involved in design activities, and what tasks and outputs should be incorporated
This Dimensional Data Modeling class is suitable for Data modelers, Business analysts and architects, Database administrators and analysts, Information technology managers and project managers, Application development project team members, People involved in design and maintenance of data warehousing and business intelligence applications, People involved in data quality or data governance processes