Join fact table with higher dimension level

Question

how do i join fact tables with higher dimension levels with discoverer?
fact with detail at level C
measure X
dimension with
D->C->B->A
E->C
level
A B C
1------1------1
2------2------1
3------2------1
join between fact X and dimension level C
X=3*C because of sum(X) in discoverer and 3xC in dimension
is there a way to get correct values for X without creating a dimension like
D->C
E->

Answer 1

another way of asking this is whether you can create a summary table in Discoverer at a higher level than a dimension's fundamental grain. In other words - the summary examples in the documentation all describe leaving out one or more of your dimensions... they are either left in or completely taken out. But, some of the most effective summarization occurs when you summarize daily data to a monthly level. Assuming that I have a sales table (at a daily level, and a key value sales_date), and a table date_dim (primary key sales_date), I would like to create a summary sales_month_summary where the sales are grouped on month_year (which is a field in the sales_date table).
How is this done? I suspect that we can't use the date_dim table with the summary (due to the problems noted by the poster above). Do we have to create another table "month_dim"? Do we have to fold all of the desired date attributes (month, quarter, year) into the summary? Obviously we'd like to re-use all of the pertinent already existing date items (quarter, month, year, etc.), not recreate them over again, which would result in essentially two sets of items in the EUL. [One used for this month summary, and another used for the detail.]
I searched the forum - someone asked this same question back in 2000 - there was no answer provided.
The only other thought I have is to "snowflake" the date_dim into two tables and two folders, one at a date level, another at the month level. Then the detail tables can connect to date_dim (which is linked to month_dim), while the summary data can connect directly to month_dim.