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Course Overview Dimensional Modelling Design is key to a successful data warehouse. Many data warehouse projects fail due to poor design. To gain the knowledge necessary to create a flexible data warehouse with optimal performance for your business, this practical course introduces the key terminology and techniques used in Dimensional Modelling. Audience This course is aimed at an audience of IT professionals who will be involved in the design, build or maintenance of a data mart or data warehouse, and need to understand the techniques involved in its design. Skills Gained - Design a data warehouse as a series of interlocking star schema data marts according to dimensional modelling design principles.
- Resolve many types of user requirements including tracking history, aggregate tables, and recursive relationships.
Prerequisites A basic understanding of relational database concepts such as joins, tables, primary keys, foreign keys, attributes and lookup tables. Course Outline Why data warehousing? - What are the main benefits of a Data Warehouse?
- Why a dimensional modelling design?
- What are the differences between Relational and Dimensional Database Designs?
- What are they each optimised for?
Approach to data warehousing - When building a data warehouse, what is the best approach to ensure the greatest returns with the least risk?
Approach to building each data mart - What is the best approach in building each Data Mart, to ensure you take into account complexities in the data?
Four types of star schema - What are the four types of star schema, and what are the benefits of each?
- What criteria should you use to compare designs?
Time dimension tips - What are the benefits of having a separate time dimension?
- Why use artificial keys?
Product dimension tips - What are the characteristics of a dimension?
Fact table tips - How should Fact tables be designed?
- What grain should you choose?
- What types of measure should you avoid?
Tracking history in a data warehouse - How would you meet requirements to ignore history, partition history, or to enable recasting of history?
- How do you adapt the approach for large or rapidly changing dimensions?
Aggregate tables - What are aggregate tables used for?
relationships - How can you meet requirements to report against a recursive hierarchy?
- What if you have a variable depth hierarchy?
Multiple fact tables - How can you record events that did NOT happen?
- What are the benefits of snapshot tables?
- How might Core and Custom tables improve the design?
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