You want to create a star schema using a calculation view. The measures are based on columns from two transaction tables. DIMENSION calculation views provide the attributes.What is the correct approach?
I recall that using an aggregation node is usually for summarizing data, so option D doesn’t seem right to me. I think it should be a join node instead.
I’m a bit confused about whether to use a star join or just a regular join for the dimensions. I feel like I’ve seen both approaches in different examples.
I think option B sounds familiar because it mentions using a join node for both the transaction tables and dimensions, which seems like a common practice question we went over.
I remember we discussed the importance of using star join nodes for combining dimensions with fact tables, but I'm not sure if it's always in a CUBE view.
This is a good test of my knowledge on star schemas and calculation views. I'll carefully read through each option and eliminate the ones that don't seem quite right.
I'm feeling pretty confident about this one. The key is to use the join node to combine the transaction tables, then the star join to link the dimensions.
Hmm, I'm a bit confused by the different nodes mentioned in the options. I'll need to make sure I understand how to properly combine the transaction tables and dimensions.
This is a tricky one. I'm torn between options C and D. Both involve using a CUBE calculation view and a star join node, but the way they handle the transaction tables is different. I guess it depends on the specific requirements of the scenario.
Hmm, I'm not sure about that. Option B looks more straightforward to me. Combining the transaction tables, then the DIMENSIONS, and using a star join node to bring it all together seems more intuitive.
I think option C is the correct approach. Combining the transaction tables using a join node in a CUBE calculation view and then using a star join node to join the DIMENSIONS to the resulting fact table seems like the logical way to create a star schema.
Jaclyn
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