How to implement fact tables with finest level of detail (fine-grained)?

Hi,
Maybe this is basic knowledge what I'm asking here... I don't know, well, here it goes:
I need to know the way carry my transactional data to a fact table, but keeping the finest level of detail possible (namely, the transactions). I implemented my cubes with MOLAP option for storage (those were the specs that I had to follow) so I can't add a unique constraint to those structures.
I only seem to be able to load aggregated, precomputed data. If I wanted to load the transactions (after the data has been transformed and clenased) where should I do it?
I tried to implement a version of the fact tables as ROLAP but got nowhere (I couldn't add a unique constraint or index on that column either).
I would really, really appreciate your help.
Best Regards,
osvaldo.
[osantos]

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?

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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?

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

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.

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

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 !

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Hello gurus,
I have a requirement to provide a report to show the consumption of available capacity per month and also YTD.
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001, 2010M02, 50
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001      2010M02     1400 (= 28 x 50)
Etc
In addition, when I add YTDCapacity to my report, the report fails with the following message:
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Did I miss any steps? Any help is greatly appreciated!
Thanks!
Randall

hi in the capacity fact table remove the level set for the calendar dim and see.

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Hi all
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I am creating one error table in oracle but i dont know how to use it in mapping.
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Webinar: How to implement secure scenarios with SAP NW PI 7.1

SAP Intelligence Platform & NetWeaver RIG APJ Expert Call
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Kind regards,
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hi,
I'm making this a sticky thread till August 18 so it will have better visibility
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