Fact tables with common and uncommon dimensions

Hi -
I have 2 facts:
F1 with Dimensions D1, D2, D3, D4
F2 with dimensions D1, D2, D5, D6
If I create a report with F1, F2, D1, D2 then 2 queries are created and the report is correct. Why am I not able to create a report with F1, F2, D1, D2, D3?
Thanks !

Hi Veeravalli -
I found this blog helpful as it details out how to establish the relation. http://108obiee.blogspot.ca/2009/08/joining-two-fact-tables-with-different.html
I had a little difficulty in understanding what you wanted to say or implement. Now, after reading it 3-4 times I figured out that you mean 1. what the blog says 2. possibility of combining the facts as different source.
As a newbie it was difficult to understand it clearly.
Thanks !

Similar Messages

Two FACT Tables, Some Common and Non-Common Dimensions

Hello all, a question i am sure you have faced in the past but still wanted to get your feedback.
I have a few FACT tables and some dimensions that are shared (common dimensions). Rest of the dimensions are related to one or the other FACT tables.
What is the best way to present a view where users can pull information from both the FACT tables?
I am successful in pulling the shared (common) dimensions across BOTH FACT tables having the same grain but this view breaks down when i pull information from one Dimension that has not much to do with the other FACT.
What is the best way to present this? Should this be broken in three subject areas?
Subject Area 1 --> Some Dims --> FACT Table A
Subject Area 2 --> Some Dims --> FACT Table B
AND
Subject Area 3 --> ***Only Common Dims*** --> FACT Table A & FACT Table B?
Your feedback is always appreciated.
Regards,
Edited by: user10679130 on Oct 12, 2009 3:27 PM

Please check the forum first for similar threads/questions.
Joining two fact tables with different dimensions into single logical table
http://108obiee.blogspot.com/2009/08/joining-two-fact-tables-with-different.html
This solution keeps both fact tables in the same subject area in the single logical fact table, with common and not-common dimensions.
Regards
Goran
http://108obiee.blogspot.com

Two Fact tables with Different set of Dimension Tables

Here is my scenario:
I got two fact tables: X and Y (actually, they are the same tables, but with different level of data)
and four dimension tables: A, B, C, D
X joins relationship to all dimensions (A, B, C, D).
Y joins relationship to only A, B, C, but no D.
When I select dimension A, B and C together with fact tables X and Y in BI Answer, result is displayed and compared.
However, if I select dimension D together with fact tables X and Y, only data from fact table X is displayed. There is no result displayed for fact table Y. I know that this is because fact table Y does not join to dimension D.
If the above relationship unchanged, how can I display both X and Y's result in BI Answer when dimension D is selected?

Thanks for all your replies.
Actually, I've tried the solutions you guys mentioned. Generally speaking, the result should be displayed. However, my scenario is a little bit tricky.
table Y's figures are not the aggregation of table X for D dimension. Instead, table Y's figures include not only D dimension total, but also others (others do not mean A, B, C dimension). For example, table Y stores all food's figure, while table X stores only drink's figure. D dimension is only about drink's detail. In my scenario, other foods' figure is not provided.
So, even if I set D dimension to all/total for table X, table X's result is still not the same as table Y.
Indeed, table Y does not have a column key to join to D dimension's key. So, if I select D dimension and table Y's measures at the same time in BI Answer, result returns no data. Hence, I can't compare table X and table Y's results with selection of D dimension.
Is there any solution to solve this problem?
Edited by: TomChan on Jun 3, 2009 9:36 AM

Load fact table with null dimension keys

Dear All,
We have OWB 10g R2 and ROLAP star schema. In our source system some rows don’t have all attributes populated with values (null value), and this empty attributes are dimension (business) keys in star schema. Is it possible to load fact table with such rows (some dimension keys are null) in the OWB mappings? We use cube operator in mappings.
Thanks And Regards
Miran

The dimension should have a row indicating UNKNOWN, this will have a business key outside of the normal range e.g. -999999.
In the mapping the missing business keys can then be NVL'd to -999999.
Cheers
Si

Modelling 2 Fact Tables with Non-Conforming Dimension in OBIEE 11g

Hi all,
I have two fact tables (Fact 1 and Fact 2) and two dimension tables (Product and Rule). The Product dimension table is a conforming dimension and is used in both fact tables, but the Rule dimension is a non-conforming dimension which is used only one fact table. I'm using OBIEE 11g (11.1.1.6.0).
====
Fact 1
====
Sales ID | Product ID | Quantity | Sales Description | Sales Status
S001 | P001 | 100 | bla bla bla bla bla | N
S001 | P002 | 200 | bla bla bla bla bla | N
S002 | P001 | 200 | lab lab lab lab lab | Y
S002 | P003 | 250 | lab lab lab lab lab | Y
Notes for Fact 1:
- One Sales ID can have multiple Product IDs
- Sales Description and Sales Status are the same for one Sales ID (repeating Sales Description and Sales Status for the same Sales ID)
====
Fact 2
====
Sales ID | Product ID | Rule ID | Score
S001 | P001 | R001 | 2
S001 | P001 | R002 | 3
S001 | P002 | R003 | 1
S002 | P001 | R003 | 1
S002 | P003 | R002 | 2
S002 | P003 | R004 | 5
Notes for Fact 2:
- One combination of Sales ID and Product ID can have multiple Rule ID
I'm wondering how best to model these tables so that I can create this report (number of the dimension and fact tables created in the business model, level mapping, aggregation rule, etc)? Any suggestion/advice on how to achieve this?
Sales ID | Product ID | Quantity | Sales Description | Sales Status | Rule ID | Score
S001 | P001 | 100 | bla bla bla bla bla | N | R001 | 2
S001 | P001 | 100 | bla bla bla bla bla | N | R002 | 3
S001 | P002 | 200 | bla bla bla bla bla | N | R003 | 1
S002 | P001 | 200 | lab lab lab lab lab | Y | R003 | 1
S002 | P003 | 250 | lab lab lab lab lab | Y | R002 | 2
S002 | P003 | 250 | lab lab lab lab lab | Y | R004 | 5
Thank you very much!

Hi Dhar, thanks for the suggestions.
I tested what you suggested, but the result is not as per my expectation mentioned above. Here's what I did:
1. In physical layer:
- I joined Fact 1 table with Product dimension table only
- I joined Fact 2 table with Product and Rule dimension tables
2. In business model layer:
- I created 3 logical tables: Fact, Product, and Rule
- The Product table contains the Product ID and Product Name from the Product dimension table in the physical layer
- I created the hierarchy (logical dimension) for Product with only ProductTotal level (as the grand total level) and ProductDetail level that contains Product ID and Product Name
- The Rule table contains the Rule ID and Rule Name from the Rule dimension table in the physical layer
- I created the hierarchy (logical dimension) for Rule with only RuleTotal level (as the grand total level) and RuleDetail level that contains Rule ID and Rule Name
- The Fact table contains 2 logical tables sources: Fact 1 (which logical level in the Content tab is mapped to ProductDetail and RuleTotal) and Fact 2 (which logical level in the Content tab is mapped to ProductDetail and RuleDetail)
- The Fact table contains Sales ID logical column (mapped to both Fact 1 and Fact 2 logical table sources)
- The Fact table also contains Sales Description and Sales Status logical columns (mapped to only Fact 1), which aggregation rule is the default to None
- The Fact table also contains Quantity logical column (mapped to only Fact 1), which aggregation rule is set to Sum
- The Fact table also contains Score logical column (mapped to only Fact 2), which aggregation rule is set to Sum
OBIEE returns the expected result when I retrieve the report:
Sales ID | Product ID | Quantity | Sales Description | Sales Status
However, OBIEE returns an error when I retrieve the reports:
Sales ID | Product ID | Quantity | Sales Description | Sales Status | Rule ID
or
Sales ID | Product ID | Quantity | Sales Description | Sales Status | Rule ID | Score
The error is:
Error Codes: OPR4ONWY:U9IM8TAC:OI2DL65P
State: HY000. Code: 10058. [NQODBC] [SQL_STATE: HY000] [nQSError: 10058] A general error has occurred. [nQSError: 43113] Message returned from OBIS. [nQSError: 43119] Query Failed: [nQSError: 14020] None of the fact tables are compatible with the query request FACT.SALES_STATUS. (HY000)
And the Score column is blank when I retrieved this report:
Sales ID | Product ID | Quantity | Sales Description | Sales Status | Score
Any suggestion anyone? Please help. Thanks a lot!
Edited by: stewartlife on Nov 29, 2012 4:01 PM

Dimension and fact table with a fact table between them

Hello all,
Here is my problem. As seen in the image, I have a fact table linked to the two dimensions.
I would have the number of Id from Cube_Requirements by variant including 'unknown" variant if no linked variant.
How is it possible ? How to create the dimension ? As my fact table has two fields, if i want to use reference as dimension usage, it doesn't work.
Thanks for your help.

Hi, this looks a many to many relationship scenario, follow these steps:
- drag extractid from cube_applicability onto measures area, so this table becomes a fact
- you will have count of Extractid measure after you perform above step
- Assuming Variant is already a dimension, go into dimension usage tab, link variant dimension with cube_requirement fact using many to many relationship and selecting cube_applicability
process cube, you should be able to get count of id by dragging and dropiping id from variant dimension..
Regards
Rakesh

Joining two fact tables with different dimensions into single logical table

Hi Gurus,
I try to accomplish in Oracle Business Intelligence 11.1.1.3.0:
F1 (D1, D2 and D3)
F2 (D1 and D2 and D4)
And we want to build a report F1 F2 D1 D2 D3 D4 to have data for:
F1 that match only for D1-D2-D3
and data for
F2 that match only D1-D2-D4
all that in one row, so D3 and D4 are not common dimensions.
I can only do:
F3 (D1, D2)
F4 (D1, D2 and D4)
And report
F3 F4 D1,D2,D4 (all that in one row, and only D4 is not a common dimension)
Here is the very good example how to accomplish the scenario 1
http://108obiee.blogspot.com/2009/08/joining-two-fact-tables-with-different.html
But looks like it does not work in 11.1.1.3.0
I get
State: HY000. Code: 10058. [NQODBC] [SQL_STATE: HY000] [nQSError: 10058] A general error has occurred. [nQSError: 43113] Message returned from OBIS. [nQSError: 14025] No fact table exists at the requested level of detail: [,,Clients,,Day,ROI,,,,EW_Names,,,,,,,,,,,,,,,,,]. (HY000)
I am sure I set up everything correctly as advised in the blog but it works with only one not a common dimension
Is it a bug in 11.1.1.3.0 or something?
Thanks,
Kate

Thanks for all your replies.
Actually, I've tried the solutions you guys mentioned. Generally speaking, the result should be displayed. However, my scenario is a little bit tricky.
table Y's figures are not the aggregation of table X for D dimension. Instead, table Y's figures include not only D dimension total, but also others (others do not mean A, B, C dimension). For example, table Y stores all food's figure, while table X stores only drink's figure. D dimension is only about drink's detail. In my scenario, other foods' figure is not provided.
So, even if I set D dimension to all/total for table X, table X's result is still not the same as table Y.
Indeed, table Y does not have a column key to join to D dimension's key. So, if I select D dimension and table Y's measures at the same time in BI Answer, result returns no data. Hence, I can't compare table X and table Y's results with selection of D dimension.
Is there any solution to solve this problem?
Edited by: TomChan on Jun 3, 2009 9:36 AM

Problem using 2 Fact tables with the same dimension

Hi,
I have noticed a very strange behaviour in Presentation Services / BI Administrator. I have 2 cubes (created in OWB) which are in the same business model, they are set up with foreign keys etc. and works as they should using them separately. Problem is (sometimes!) when I want to use the common dimension (Project) against both of the fact tables (Sales Order and Purchase Order).
Scenario 1:
If I use Project Id, Purchase Amount, Sales Amount I get either an amount in Sales Amount or in Purchase Amount, BUT if the Project Id starts with a letter (not starting with a number) it will show the correct amount for both Sales- and Purchase Amount.
Scenario 2:
I use Project Description (even followed by Project Id or not), Sales Amount, Purchase Amount I get the correct numbers for all projects. Project Description must come before Project Id or else it will not work.
I only noticed this problem when using both of the Fact tables since I want to compare Sales Amount and Purchase Amount in each Project. The Dimension for Project consist of Project, Sub Project and Activity and works fine. If I only use Sales Amount or Purchase Amount with Project Id I don't get this error. Only when both numbers are used.
I would be very happy if anyone have a good solution/explanation to this problem! Seems like could be something in the BI Server memory that goes wrong somewhere.

The strange thing is that the results from the queries are correct running them in SQL Developer. This is one that works:
SELECT Project.Project saw_0, "- SalesOrderFact"."Sales Amount" saw_1, "- PurchaseOrderFact"."Purchase Amount" saw_2, REPORT_SUM(saw_1 BY ), REPORT_SUM(saw_2 BY ) FROM SalesOrder ORDER BY saw_0
SALES ORDER:
select T3032.PROJECT_DESCRIPTION as c1,
sum(T161.SALES_AMOUNT_LOCAL) as c2
from
DIM_PROJECT_V T3032,
CUBE_SALES_ORDER T161
where ( T161.DIM_PROJECT = T3032.DIMENSION_KEY )
group by T3032.PROJECT_DESCRIPTION
order by c1
PURCHASE_ORDER:
select T3032.PROJECT_DESCRIPTION as c1,
sum(T3020.TOTAL_BUY_AMOUNT) as c2
from
DIM_PROJECT_V T3032,
CUBE_PURCH_ORDER T3020
where ( T3020.DIM_PROJECT = T3032.DIMENSION_KEY )
group by T3032.PROJECT_DESCRIPTION
order by c1
And this will give the wrong result in Answers (correct in SQL..):
SELECT Project."Project Id" saw_0, "- SalesOrderFact"."Sales Amount" saw_1, "- PurchaseOrderFact"."Purchase Amount" saw_2, REPORT_SUM(saw_1 BY ), REPORT_SUM(saw_2 BY ) FROM SalesOrder ORDER BY saw_0
SALES_ORDER:
select T3032.PROJECT_KEY_NAME_ID as c1,
sum(T161.SALES_AMOUNT_LOCAL) as c2
from
DIM_PROJECT_V T3032,
CUBE_SALES_ORDER T161
where ( T161.DIM_PROJECT = T3032.DIMENSION_KEY )
group by T3032.PROJECT_KEY_NAME_ID
order by c1
PURCHASE_ORDER:
select T3032.PROJECT_KEY_NAME_ID as c1,
sum(T3020.TOTAL_BUY_AMOUNT) as c2
from
DIM_PROJECT_V T3032,
CUBE_PURCH_ORDER T3020
where ( T3020.DIM_PROJECT = T3032.DIMENSION_KEY )
group by T3032.PROJECT_KEY_NAME_ID
order by c1
As you can see the SQL look very familiar, and I cannot see anything in SQL that should be the cause of this error. I think the error must be in the BI Memory or something.
Any ideas?

Join fact table with higher dimension level

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->

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.

Logical fact table with fragmented data sources with different dimensions

Hello.
I have a logical fact table with four logical table sources. Three of the LTS's share the same dimensions, but the fourth LTS has one dimension (called Dim_A) less. In the physical layer the dimension Dim_A is joined to the first three physical fact tables, but not to the fourth fact table (since it doesn't have that dimensionality). In the BMM layer the logical fact table is joines to the logical dimansion Dim_A.
When I run an analysis on this RPD the measures from the logical fact is aggregated correctly (union of all four table sources) as long as I doesn't include Dim_A, but as soon as I include dimension Dim_A I get the error message:
+State: HY000. Code: 10058. [NQODBC] [SQL_STATE: HY000] [nQSError: 10058] A general error has occurred. [nQSError: 43113] Message returned from OBIS. [nQSError: 43119] Query Failed: [nQSError: 14052] Internal Error: Logical column Dim_A.Column_X has no physical sources that can be joined to the physical fact table source [Logical table sources (Priority=0): Fact_B.Fact_Y]. (HY000)+
I would like a solution where the analysis returns correctly aggregated measures also for the LTS with the "missing" dimension, but with a dimension value NULL for this LTS. Or something like this.
Is there a way to set this up in the RPD.
Thanks,
Henning Eriksen

The SQL could look something like this.
SELECT dim_a.col_1, fact_a.measure_1
FROM db.dim_a
JOIN
db.fact_a
ON fact_a.col_2 = dim_a.col_2
WHERE fact_a.date = '28-nov-2012'
UNION ALL
SELECT dim_a.col_1, SUM (fact_b.measure_1)
FROM db.dim_a
JOIN
db.fact_b
ON fact_b.col_2 = dim_a.col_2
WHERE fact_b.date = '28-nov-2012'
UNION ALL
SELECT dim_a.col_1, SUM (fact_c.measure_1)
FROM db.dim_a
JOIN
db.fact_c
ON fact_c.col_2 = dim_a.col_2
WHERE fact_c.date = '28-nov-2012'
UNION ALL
SELECT NULL, SUM (fact_d.measure_1)
FROM db.fact_d
WHERE fact_d.date = '28-nov-2012'
I would appreciate if you could give me some hints for the RPD.
Thanks,
Henning

Fact Table with a metric repeated in several rows

Hi!!
I've got a little problem and I don't know how to face it.
I'm using OBIEE and I've got this case:
One fact table like this:
Order_Number - Q.Received - Supplier - Invoice_Number - Q.Inv.
1 - 10 - S1 - I1 - 2
1 - 10 - S1 - I2 - 8
2 - 10 - S1 - I3 - 10
So, for an order Number, I can have more than one Invoice Number, but the quantity Received is always 10, because is a metric refered to the Orden, not to de Invoice, but this quantity (10) I find it in two rows, not in one row. It's like having two fact tables mixed (invoices and orders).
My problem is:
If in the logical field Q.Received I don't aggregate de column, when in Answers I try to know the Quantity of units received by supplier S1, the report says 10, that is incorrect. It should be 20.
If in the logical field Q.Received I aggregate de column, when in Answers I try to know the Quantity of units received by supplier S1, the report says 30, that is incorrect too.
I've tried to separate it in two fact tables by views like this:
Fact1: Orders
Order_Number - Q.Received - Supplier
1 - 10 - S1
2 - 10 - S1
Fact2: Invoices
Order_Number - Invoice_Number - Q.Inv.
1 - I1 - 2
1 - I2 - 8
2 - I3 - 10
...and I've created a dimension with Order_Number, but the report:
Order_Number - Q.Received - Q.Inv.
...doesn't work.
-If I try without jerarquies, OBIEE goes only to the first one and if I select a field from Fact2 says that there isn't a mapping for this field.
-If I try with jerarquies for the only dimension I have, with a grand total level and a child level, selecting the lowest level for all tables, error is: "None of the fact tables are compatible with the query request "
Can anybody help me? I'm having nightmares with this issue.
Thanks a lot in advance.

Hi,
Okay. I assume you have the 2 facts:
Fact1: Orders
Order_Number - Q.Received - Supplier
1 - 10 - S1
2 - 10 - S1
Fact2: Invoices
Order_Number - Invoice_Number - Q.Inv.
1 - I1 - 2
1 - I2 - 8
2 - I3 - 10
create a business model with the following logical tables:
Order Dim,
QTY Received,
QTY Invoiced
drag/drop Order_number from Fact1 to the logical table Order Dim (this will create a logical column Order_number).
drag/drop Order_number from Fact2 to the logical COLUMN Order_number. (This will give you a second Logical Table Soruce with 1 logical table column.)
drag/drop Q.Received from Fact1 to logical table QTY Received
drag/drop Q.Inv. from Fact2 to logical table QTY Invoiced
Assign key to LT Order Dim
and draw Business Model Diagram.
This should give you the possibility to report the quantity received and invoiced per order number
Regards
Message was edited by:
wobiee1

How to handle Fact tables with different granularity in OBIEE 11g RPD

Hello Everyone,
I have got stuck here and need your help.
I have two fact tables (Say F1 and F2... F1 is containing data at month-level and F2 is containing data at day level) and one Date DIMENSION TABLE. Date_Code is the PK of Date dimension table.I need to use time-series functions also.
Can anyone tell me how to model this requirement in the RPD.
Can we use a single dimension table(Here Date dimension table) with two fact table of different grainularity? What would be the best way to implement this requirement?
Thanks in advance :)

Hi Veeravalli,
Thanks for your reply :)
Let me explain the problem in more detail. I have one Date dimension(Date_Code,Month_Code,Quarter_Code,Half_Year_Code,Year_Code). Here Date_Code is the PK.
In F1---->Date (Using Month_Code key)
F2-------->Date (Using Date_Code Key)
Level based hierarchy is there starting from Year to Date.Each level has PK defined and chronological key selected.
F1 has level set to Month and F2 has level set to Day.
Now if i am using ago() function on measure of F2 (having day level data) then it's working fine but if i am using ago() function on measure of F1...I am getting an error at Presentation service: Date_code must be projected for time-series functions.
So the whole issue is with time-series functions. As per my research...I think for time series the tables in the physical model containing the time dimension cannot join to other data sources, except at the most detailed level but here i am joining with F1(using Month_Code which is not the most detailed level).
So kindly let me know how to achieve this in rpd?

Select count from large fact tables with bitmap indexes on them

Hi..
I have several large fact tables with bitmap indexes on them, and when I do a select count from these tables, I get a different result than when I do a select count, column one from the table, group by column one. I don't have any null values in these columns. Is there a patch or a one-off that can rectify this.
Thx

You may have corruption in the index if the queries ...
Select /*+ full(t) */ count(*) from my_table t
... and ...
Select /*+ index_combine(t my_index) */ count(*) from my_table t;
... give different results.
Look at metalink for patches, and in the meantime drop-and-recreate the indexes or make them unusable then rebuild them.

Using expdp to export a mix of tables with data and tables without data

Hi,
I would like to create a .dmp file using expdp, exporting a set of tables with data and another set without data. Is there a way to do this in a single .dmp file? For example, I want all the tables in a schema with data, but for the fact tables in that schema, I only want the fact table objects, not the data. I thought it might be easier to create two separate .dmp files, one for each scenario, but would be nice to have one .dmp file that satisfies my requirement. Any help is appreciated.
Thanks,
-Rodolfo
Edited by: user6902559 on May 11, 2010 12:05 PM

You could do this with where clauses. Let's say you have 10 tables to export, 5 with data and 5 without data. I would do it like this
tab1_w_data
tab2_w_data
tab3_w_data
tab4_w_data
tab5_w_data
tab1_wo_data
tab2_wo_data
tab3_wo_data
tab4_wo_data
tab5_wo_data
I would make one generic query
query="where rownum = 0"
and I would make 5 specific queries
query=tab1_w_data:"where rownum > 0"
query=tab2_w_data:"where rownum > 0"
query=tab3_w_data:"where rownum > 0"
query=tab4_w_data:"where rownum > 0"
query=tab5_w_data:"where rownum > 0"
The first query will be applied to all tables that don't have their own specific query and it will export no rows, the next 5 will apply to each of the corresponding table.
Dean

Fact table with different granularity

I have a fact table , the measure with different granualrity , for example, there are a fact table named project, and in the project , there are some columns measure like project value, Opportunity value, (one opporuntity have many project). so I have to sum the project value and Opportuntity value
by month, how to sum opportuntity value? (I want to sum the value distinct Opportuntity ). anyone have suggetion. thanks in advance.

The purist answer is that you should NEVER have a fact table with multiple levels of granularity - it's asking for trouble. Better solution is to split off a new fact table at the proper level of granularity. Having said that, I've worked with BI Apps before so I understand the pain you're going through. In the long run though we found it better to add new fact tables and track the data at the proper levels. Less confusing (long run) than trying to kludge round data to fit in a square fact table.
Thx,
Scott

Fact tables with common and uncommon dimensions

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