I'm brand new to OLAP. I'm using OLAP Services under MS SQL 7.0. So I hope this forum is close enough of a match to answer my question.
I'm trying to design a cube that shows Sales for different dimensions across a company. Lets say my company is made up of the following: District 1 which has stores 1 and 2 under it, and district 2 which has stores 3 and 4 under it.
My problem is that when I drill down into the data with a district dimension and a store dimension set up. I can drill down to show data for something illogical such as District 1, Store 4. Using two different dimensions (district and store) is it possible to restrict the choices of one dimension based on the choice of another? (i.e. if I pick District 1, I only want to be able to drill down to stores 1 and 2).
I know I can combine my hierarchy into one dimension (something like DistrictStore which has district and stores nested together), but then I run into a problem if I want to view data across all stores for example.
When used to using SQL as a normal flat database for years, going into OLAP is enough to make your head spin.
Thanks,
Bob
I'm trying to design a cube that shows Sales for different dimensions across a company. Lets say my company is made up of the following: District 1 which has stores 1 and 2 under it, and district 2 which has stores 3 and 4 under it.
My problem is that when I drill down into the data with a district dimension and a store dimension set up. I can drill down to show data for something illogical such as District 1, Store 4. Using two different dimensions (district and store) is it possible to restrict the choices of one dimension based on the choice of another? (i.e. if I pick District 1, I only want to be able to drill down to stores 1 and 2).
I know I can combine my hierarchy into one dimension (something like DistrictStore which has district and stores nested together), but then I run into a problem if I want to view data across all stores for example.
When used to using SQL as a normal flat database for years, going into OLAP is enough to make your head spin.
Thanks,
Bob