You are developing a SQL Server Analysis Services (SSAS) cube for the sales department
at your company.
The sales department requires the following set of metrics:
Unique count of customers
Unique count of products sold
Sum of sales
You need to ensure that the cube meets the requirements while optimizing query response
time.
What should you do? (Each answer presents a complete solution. Choose all that apply.)
A.
Place the measures in a single measure group.
B.
Place the distinct count measures in separate measure groups.
C.
Use the additive measure group functions.
D.
Use the semiadditive measure group functions.
E.
Use the Count and Sum measure aggregation functions.
F.
Use the Distinct Count and Sum measure aggregation functions.
B and F
I agree
I also agree
without doubt B & F. Sum of sales would be a fully additive measure and best practice is to put all distinct count measures in separate measure groups for performance.
‘What should you do? (Each answer presents a complete solution. Choose all that apply.).’
each answer must present complete solution-> only F?, B only takes of distinct count, but no SUM
My comprehension is that if you apply B (each distinct count measure in separate measure groups.) then your “Sum measure” will be in another measure group… so it works even if it is not specified… :/
B & F ok
but you also need
– C for the additive behaviour of the Sum
– D for the semi-additive behaviour of the distinct counts
on 2nd thought: C is too much. A sum has by default the additive property.
So B & F but somehow I think you also need D. Anyone ?