In a purely dimensional modeling effort we have a need to obtain data from multiple fact tables to complete the report as the clients need it. One would generally say well just join on common dimensions. The problems that I see with this approach is:
I see potentially two approaches to solve this issue.
What is your opinion?
Larissa Moss' Answer: This is a classic example of why a data warehouse environment is not - and should not be - all about multidimensional designs only! I rest my case.
Les Barbusinski's Answer: Option 1 is the way to go. It's common - and, often, desirable - to have similar fact tables in a data mart which a) have different perspectives, and/or b) are designed to answer slightly different questions in an efficient manner. Dynamically joining six fact tables to calculate a metric serves no purpose if the report takes forever to generate and/or degrades the overall performance of the mart.
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