July 14, 2015 at 10:01 am
Hi everyone,
I am new in the BI world and I would have these questions:
- Is it possible to have a MDX query that restrict (WHERE CLAUSE) based on a column's value that is in a fact table?
- When we have a measure in a dimension does it mean we have to revised or star schema?
Best regards.
Carl
July 14, 2015 at 10:12 am
Carl B. (7/14/2015)
Hi everyone,I am new in the BI world and I would have these questions:
- Is it possible to have a MDX query that restrict (WHERE CLAUSE) based on a column's value that is in a fact table?
- When we have a measure in a dimension does it mean we have to revised or star schema?
Best regards.
Carl
Not sure what you're looking for in the first question.
If you have measures in your dimensions then you really need to review your design. Measures belong in the fact table(s), not in dimensions.
For best practices on asking questions, please read the following article: Forum Etiquette: How to post data/code on a forum to get the best help[/url]
July 14, 2015 at 10:26 am
"Is it possible to have a MDX query that restrict (WHERE CLAUSE) based on a column's value that is in a fact table?"
Lets give an example:
Lets say we want to count the number of items in the fact table that have -1 <= deviation_time <= 3 for all item that have source = 'AMS'.
deviation_time and source being two columns in the fact table.
Do we have to reconsider our design here also?
Best regards.
Carl
July 15, 2015 at 5:34 am
Please read about:
1. Degenerate dimensions
2. Junk dimensions
3. MDX Subcube (or sub query)
Raunak J
July 15, 2015 at 6:13 am
Quote from Kimball on what they refer to as Measure Type Dimensions:
Sometimes when a fact table has a long list of facts that is sparsely populated in any individual row, it is tempting to create a measure type dimension that collapses the fact table row down to a single generic fact identi?ed by the measure type dimension. We generally do not recommend this approach. Although it removes all the empty fact columns, it multiplies the size of the fact table by the average number of occupied columns in each row, and it makes intra-column computations much more difficult. This technique is acceptable when the number of potential facts is extreme (in the hundreds), but less than a handful would be applicable to any given fact table row.
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