Dimensional data is a core component of modern business intelligence and analytics. It is widely accepted as a proven and practical way to design and implement business measures and metrics. Dimensionally organized data provides a strong foundation for performance dashboards and scorecards, and offers a more effective and adaptable solution to business analytics needs than can be achieved with relational data structures.
Over three days of in-depth, interactive training, the Dimensional Data Modeling Skills workshop will provide your team with comprehensive coverage of dimensional modeling principles, processes, and deliverables, from the author of Star Schema: The Complete Reference. Starting from the basics, learn a complete set of best practices—from multiple fact table designs, to bridge tables, to advanced slow change processing. Build the skills to match these techniques to real-world business complexity and apply them to solve real modeling problems. Learn how to fit dimensional modeling into agile development frameworks. You’ll receive templates to capture requirements and designs and complete the class with a robust understanding of dimensional data modeling pragmatics.
There are no prerequisites for this course.
Professionals who need a comprehensive understanding of dimensional data modeling and star-schema design:
BI program managers
Data architects and modelers
BI architects and developers
Data integration architects and developers
“Power users” and business subject matter experts
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