SSAS - Many to Many Relationship Grain Filters Out Data (Many to One)
I have a simple Many to One example: One Fact Table record has many Dimensional Items. The Example I'm using is One FactEvent record can have multiple EventMembers. These members are always unique so the relationship is really many to one (vs.
many to many). The grain of the Fact is one row for every event. Not all events have members, but I have stubbed those with -1
I tried using a Referenced dimensional relationship, but it threw my total counts off. I decided to make it more complicated by using a
Many to Many relationship, but I had issues once I started slicing the data.
The following are my two very simple tables:
FactEvents:
EventMemberID MemberKey EventMemberKey MemberName MemberGender
1 1 -1 None N
2 2 E2 Tyler M
3 3 E2 John M
4 4 E2 Sue F
5 5 E5 Tim M
6 6 E5 Jane F
7 7 E12 Ashley F
8 8 E12 Jessica F
9 9 E12 Kristy F
10 10 E17 Mike M
11 11 E17 Josh M
12 12 E18 Warren M
13 13 E18 Eric M
Here is the bridge Table:
EventID EventBK EventName EventMemberKey EventCount
1 E1 Hockey Game -1 1
2 E2 Soccer Game E2 1
3 E3 Baseball Game -1 1
4 E4 Concert -1 1
5 E5 Food Festival E5 1
6 E6 Movie Night -1 1
7 E7 Data Group Event -1 1
8 E8 City Tour -1 1
9 E9 Ski Trip -1 1
10 E10 Camping Trip -1 1
11 E11 Hiking Trip -1 1
12 E12 Community Cleanup E12 1
13 E13 Block Party -1 1
14 E14 Toastmasters -1 1
15 E15 Train Spotting -1 1
16 E16 Plane Spotting -1 1
17 E17 Fishing Trip E17 1
18 E18 Hunting Trip E18 1
19 E19 Street Hockey -1 1
20 E20 Bonspiel -1 1
You can see many events have no members and some events have multiple members. There is not separate members Dim, just the bridge table. I tried to build view that would work as bridge tables, but it started to feel like overkill.
Here is the SSAS structure:
Cube:
I tried creating a bridge Dim and Measure Group that can be used to join FactEvents with DimMemberEvent:
When I query the database tables directly, I can get the structure I'm looking for:
Gender Count
F 5
M 7
N 15
This represents that although there are 20 events, there were 5 Female and 7 Male participants and 15 events with No participants. When looking at the cube in excel I get:
Gender Count
F 3
M 4
N 15
Grand Total 20
The grand total is correct, however, it looks like it is grouping the events, so if there are multiple Female members at a particular event, they get rolled up. You can see this better if I pull in member name:
It includes all the names with count 1 ie. 5 Females with count 1, but the gender subtotal is 3 (as it is grouping the gender dimension)
The detail member counts are good, but the rolled up M and F counts are stripping out duplicates. Is there a way to model this in SSAS to preserve the detail member counts when the member dimension is used? Is a many to many the best solution?
This is all using SQL Server 2012 Multi-Dimensional Model. Thanks.
Ok, for starters, if it's a one to many relationship, don't set it up as a many to many! Avoid many to many relationships and really anything other than "regular" relationships.
Second, the tables you pasted the data for aren't the tables you are describing them as, based on the dsv screenshot you included. If your post is confusing to the people who are wanting to help you, they will quickly move on.
It seems that you are not clear on how to construct a star schema. I will lay one out for you and hopefully this can help you on your journey.
fact_member_event:
event_id
member_id
member_event_count
dim_member:
member_id
member_key
member_name
member_gender
dim_event:
event_id
event_name
fact_event:
event_id
event_count
Or alternately, you could drop the fact_event fact table and have a calculated member that uses dimEvent.event.event.allmembers.count. It's a little bit of a weird situation that I would want to play with, but I would start with the above.
Also if you post back and show query results, you should make it clear what columns you are displaying. I see "count" in your query above, but nowhere in the star schema do I see "member count"
as a field.. I guess that's event count?
Hope this helps,
Ken
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