What is the difference between a Conformed Dimension and a Junk Dimension in Dimensional Modeling?
- Conformed dimensions are normalized
- Conformed dimensions are shared across multiple data marts
- Junk dimensions represent high-cardinality attributes
- Junk dimensions store miscellaneous or low-cardinality attributes
Conformed dimensions in Dimensional Modeling are dimensions that are consistent and shared across multiple data marts or data sets, ensuring uniformity and accuracy in reporting. Junk dimensions, on the other hand, contain miscellaneous or low-cardinality attributes that don't fit well into existing dimensions.
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