Linking 2 facts with common dimensions

Dear all,
Request you help in this.....
I have the following tables as facts and dimensions in the physical layer
Facts: Order, Shipment
Dimensions : Product
1) I have linked each of the facts with the dimension in the physical layer.
2) I brought the model into the BMM layer with the same joins on dimension and facts as in physical layer, but gave a complex join.
now my question is:
1) If I want to have the order and shipment fact data together along with the dimension data , what all the steps I need to follow?
2) I already tried creating hierarchies to the dimension (which is conformed) and set the aggregation level to the lowest in the facts. It didnot work.
Could you please help me in this.
Thanks,
Suma

Yes ..If I do that .. I will get the results...
but the scenario I presented here is only a part of the actual requirement.
Now.... I have 6 dimensions and 8 fact tables....
few concerns...
1) Would the above solution be feasible making a single fact source for all the 8 facts? Even though we take only the required columns ,
the table structure will become huge...
2) Also for all the fact tables I need to give an outer join as per the business requirement
(Ex: an Order is made and it is not shipped yet.. so the shipment table will not have any entries for that Order.. so Order and shipment tabls are to be given an Outer join in the content tab of LTS)
so if I give outer join for all the facts I need, performance will drastically come down as the query makes a full table scan for all the 8 facts.
Is there any other way to get this done, keeping all the facts as separate fact tables only in BMM and joined on all the dimensions?

Similar Messages

2 Facts with common dimensions

Hi All,
I am trying to developer an Answer
I have two Fact tables :- Budgets and Actuals
The two Fact Tables have common dimensions (Period, Cost Centre and Expense)
When I create an answer which combines these common dimensions and the two fact tables I can create a report that compares Actuals Vs Budgets and that works fine
However the Budget Fact has an additional dimension Bugdet Name (which can have values like 'Budget','Forecast','Allocation') that does not apply to Actuals
When I try to fliter or include the Budget Name I lose all my actuals
(Incidentally some actuals do not have budgets, some budgets do not have actuals and I want to see all rows)
Any ideas?
Cheers
Pete

Hi,
I try this:
I have in BMM one subject area with two fact and common dimension
SALES -> quantity_sold measure
and
SALES_TIME_ID -> select (amount_sold-100) as amount_sold, time_id from sales
and dimensions
TIMES
PRODUCTS
Both are joined to a SALES and just TIMES is joined to a SALES_TIME_ID in physical layer and in BMM complex join are propagated from facts to dimensions
Test in Answers - both queries are generated:
TIMES.CALENDAR_YEAR
SALES.QUANTITY_SOLD
SALES_TIME_ID.AMOUNT_SOLD
select T20553.CALENDAR_YEAR as c1,
sum(T20550.QUANTITY_SOLD) as c2
from
TIMES T20553,
SALES T20550
where ( T20550.TIME_ID = T20553.TIME_ID )
group by T20553.CALENDAR_YEAR
order by c1
------------------- Sending query to database named orcl (id: <<13806>>):
select T20553.CALENDAR_YEAR as c1,
sum(T35447.amount_sold) as c2
from
TIMES T20553,
(select (amount_sold-100) as amount_sold, time_id from sales) T35447
where ( T20553.TIME_ID = T35447.time_id )
group by T20553.CALENDAR_YEAR
order by c1
PRODUCTS.PROD_CATEGORY
TIMES.CALENDAR_YEAR
SALES.QUANTITY_SOLD
SALES_TIME_ID.AMOUNT_SOLD
select distinct D1.c2 as c1,
D1.c3 as c2,
D1.c1 as c3,
cast(NULL as DOUBLE PRECISION ) as c4
from
(select sum(T20550.QUANTITY_SOLD) as c1,
T20553.CALENDAR_YEAR as c2,
T21473.PROD_CATEGORY as c3
from
TIMES T20553,
PRODUCTS T21473,
SALES T20550
where ( T20550.PROD_ID = T21473.PROD_ID and T20550.TIME_ID = T20553.TIME_ID )
group by T20553.CALENDAR_YEAR, T21473.PROD_CATEGORY
) D1
order by c1, c2, c4
Amount sold is null because SALES_TIME_ID does not contain PROD_CATEGORY attribut, it's not common.

How to Link two Facts with Different Time Granularity (Year, Quarter) to a Single Time Dimension

Hello All,
I have the below scenario where i have Two Facts Fact Quarterly and Fact Yearly but one Time Dimension which has Quarter grain.
So my question is how do i Establish relationship from Fact Yearly to Time Dimension??
Ex:

Hi naveej,
According to your description, you want to know how to build the relationship with time dimension and fact tables. Right?
Based on your screenshot, it's better to have only one fact table for sales and build the relationship with time dimension. To determine quarterly or yearly data only depends on how you slice the time dimension. However, I notice that the Revenue for year
is different from the aggregated Profit for quarters. If the Revenue and Profit are different measure, you need to have two fact tables. And you should build the relationship (Regular) between TimeDim and FactYearly on YYYY attribute.
Reference:
Defining a Fact Relationship
Best Regards,
Simon Hou
TechNet Community Support

Joining Two facts with one dimension

hi,
Hello Experts,I am reporting out of 2 fact groups.
Mailing History and Booking.
The only common dimension between the 2 is the Person Dimension. I have created the hierarchies and defined the aggregation content in the LTS.This helps me in reporting using any column from the Facts or any one dimension from either of the fact groups. But if i select 2 or more dimensions , one or more from each fact group , then the report gives and error. A general error has occurred. [nQSError: 14026] Unable to navigate requested expression: MailingHistory Campaign.Campaign Name. Please fix the metadata consistency warnings. (HY000)
For Example : BookingDim--BookingFact-MailingHistoryFact (ok) MailingSourceDim--BookingFact-MailingHistoryFact works (ok) but BookingDim--BookingFact-MailingHistoryFact - MailingsourceDim (Fails ).
When i am applying the filter from the fact 1 . i am getting this error.(which is the column in the second fact table 2).I checked all the joins in the BMM layer.
Please help me!!!
Thanks,
Surya

Surya did you set the levels properly for two fact tables and also for metrics.
When ever you are using two fact groups with non confirmed dimensions you have to make sure all the content levels set for the fact tables and as well as for metrics.
in your fact tables/ metrics - For related dimensions set the level to Detail. and for the non related dimension set the level to Total. This way obiee server will understand what is related dimension and whats not related..
hope this works for you.

Two facts with conformed dimension

Starting new thread per Alistair's request :)
I have two facts
Class Enrollment (who is enrolled in which classes)
External Test Scores (who got what score on what exam)
The only dimension they have in common is "Person".
Is it possible to build a presentation layer that includes both facts, the Person dimension, and dimensions that related to one fact but not the other (e.g. dimension "External Test Type" or dimension "Course")?
How would I set up the BI metadata to answer the question:
What was the average grade for Course ABC for students who scored above a 50 on test XYZ?
So far, for External Test Scores fact, I have created hierarchies(/dimensions) for any related dimension tables that didn't already have hierarchies defined. I then went to the Content tab for External Test Scores and set aggregation levels (lowest level for everything related to the fact, "total" level for everything NOT related to the fact).
I put both facts and the "Person" dimension into a presentation folder. I can query test scores ok, but when I add in a simple "Row Count" column from class enrollment, I get no data back.
Do I now go back and do the same Content tab settings for the Class Enrollment fact? My initial attempts at this yielded consistency check warnings of "Logical table source does not join to any fact source".
Huge thanks for suggestions.
-John

Hi John,
I tend to harp on a lot about the need for a hierachy on every logical dim, even just total -> detail. It allows this (non-conformed) approach for starters, also allows another developer to quickly ascertain the relationship between objects.
About the complex joins, I meant do as you will have done for a normal star with just the conformed dims, so thats Foreign keys where applicable in the Phyiscal layer, and Complex joins where applicable in the BMM layer. I just wanted to make a point that you should do this as per a normal normal star schema with fully conformed dimensions, and merely that the none-conformed dimension will only be connected to its relevant fact table - probably didnt need to say it as it may be more confusing!
Your correct with aggregation rules, ideally all objects in a logical fact should have an aggregation rule - otherwise it should be in a logical dimension.
As to the approach, this is the way i've always handled non-conformed dimensions when the requirement is to see both facts on the same report. Our Peak Indicators OBIEE training material on this subject is as follows :
"order" fact table, dimensioned by Date, Customer, Product.
"inventory" fact table dimensioned by Product only.
Report requirement - Show me all orders where the order_qty (order fact) is greater than the total qty in stock (inventory fact)
So like your example, we sum up both qty's and use a where clause to filter only rows where one fact measure is greater than another measure.
Whats the ideal approach ??
If you had control of the ETL perhaps you could seed an 'unknown' record in the non-conforming dimensions, and then reference this on the other fact table, but I'd say the majority of the time, the customer who wants everything by everything in their subject area needs a little education, its really not good for end users having 10's of folders with 10's of columns - we should be creating analysis subject areas to enable the answering of business questions, theres no reason why we cant combine reports from different subject areas on one dashboard page, all using a common set of prompts, but there really isnt a need to give an end user the whole BMM / DW etc in one go.......unless they are paying of course, and after you've tried to educate them they want it there way :-)

2 facts with different dimensions in 1 logical table

hello,
im trying to accomplish the set up as described per blog:
http://108obiee.blogspot.com/2009/08/joining-two-fact-tables-with-different.html
i.e. i have 2 facts, F1: D1 ; F2: D1,D2,D3;
i followed the instructions and all seem to be working fine;
however: when i put the total on the report in Answers: D1,D2, F1, F2 then the measures from F1 that are repeated every row for D2 are being added , like regular sum on the column; this is not correct;
the only correct result i can get if manually i change the Aggregation Rule to :Server Complex Aggregate on all F1 measures;
id like to ask if this is a bug of this OBI version? 10.1.3.2
i wish not to instruct my users to change the aggregation rule; id like to have the set up via rpd such, that they dont have to manipulate the aggregation rules;
did anyone got the above working with correct totals without changing the aggregation rule?
if so, id appreciate any tips on how to achieve that
thanks
rgds

Basically, you need to :
* create your physical schema with the relationship
* drag and drop your Forecast Facts measure in the same logical table than your sales fact
* define your Forecast measure as level based measure (logical column/levels/properties) with the grain of the forecast table
Documentation
http://download.oracle.com/docs/cd/E12103_01/books/admintool/admintool_BusModSetup12.html
And you have an example in OBE series with quota in excel sheet :
http://www.oracle.com/technology/obe/obe_bi/bi_ee_1013/bi_admin/biadmin.html#t8
Success
Nico

Multiple Date Fields (Fact Table) - Linking with Time Dimension

I have a fact table that has multiple date columns.
I can make a time dimension, but it has to be joined to a particular date column. This becomes difficult because of the limit in having multiple date fields reference one time dimension. I can see possibly
creating a date table which contains all dates, link to fact as well as time dimension table. I am trying to better visualize the table layout on this one. Or are there possibily better ways of looking at this senerio
Any idea's

Figured this one out; going to use one time dimension - what looking too much into the details in regard to this scenerio

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

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

Multiple facts with shared/non shared dimensions

Hello All,
I have a scenario where we are using multiple facts in OBIEE. Fact1(Inventory Onhand) is joined to all shared dimensions, and Fact2( Forecasting Values) is joined to few shared dimesnions so the joins are like:
Fact1 with Dim1, Dim2, Dim3, Dim4, Dim5, Dim6..
Fact2 with Dim1,Dim3, Dim5
I have given the physical joins in the physical layer, later in the logical layer I pulled the fact2 in to to the fact1(multiple LTS) and then set the aggregattion levels for the non conformed dimensions. This was working fine for me but the customer was not happy with this. He doesnt want to have different levels of data in to a single fact.
What are the allternate possible solutions to implement this in the busines layer?
Any ideas/inputs are highly appreciated.
- Abhi

Hi,
I have done the same as explained above. But here the issue is we are getting duplicate data.
For Ex: if i have one common dimmension attribute and two non confirmed dimension attributes with a measure. For non confirmed dimension have different value and for all these values the common dimension attribute is same. Then the common attribute will repeat for all non confirmed dimensions.so, here automatically the Corresponding measures also repeating.
Common Attr non-Confirm Attr1 non-Cnfirm Attr2 measure
123 abc xyz 1000
123 bac yzx 1000
123 pqr mno 1000
If you observe the above exapmple the confirm dime attr is same for both non confirm dime attrs, so the measure values also repeating here. If i see the data base i have measure data only for ABC record. For Remaining two records it is 0, but here the value 1000 is showing for remaining two records as well.
Please let me know if any one face this issue earlier.
Regards,
Aari

Forcing full outer join between two facts according to common dimensions

Hi everyone,I have an issue with the way obiee "joins" 2 fact tables regarding according to common dimensions.
Let's assume 2 fact tables F1 and F2 and 2 dimension D1 and D2.
Fi is joined to Dj thanks to IDs.
F1 and F2 have got aggregates sum(mes1), respectively sum(mes2).
The group by is performed on dim1 for D1 and dim2 for D2.
The following 2 queries work fine...but separately:
select dim1, dim2, sum(mes1) from F1, D1, D2 where ... group by dim1, dim2; //7 lines
select dim1, dim2, sum(mes2) from F2, D1, D2 where ... group by dim1, dim2; //8 lines
When I try to select dim1, dim2, sum(mes1) and sum(mes2), the following sql is created by the BI server:
WITH SAWITH0 AS (
select dim1, dim2, sum(mes1) c3 from F1, D1, D2 where ... group by dim1, dim2
), SAWITH1 AS (
select dim1, dim2, sum(mes2) c3 from F2, D1, D2 where ... group by dim1, dim2
select ... dim1,
     ... dim2,
     ... SAWITH0.c3,
     ... SAWITH1.c3
FROM SAWITH0 LEFT OUTER JOIN SAWITH1
     on SAWITH0.dim1=SAWITH1.dim1 and SAWITH0.dim2=SAWITH1.dim2
I get only 7 lines. It means I miss one line from the second query on F2.
The solution is to perform a full outer join. (I tried in TOAD and changing LEFT by FULL is ok)
How can I force the full outer join?
Thanks a lot!

If you use the fact vertical capabilities of OBIEE, it will normally perform a full outer join :
http://gerardnico.com/wiki/dat/obiee/logical_sql/obiee_full_outer_join
Check here for an example (replace the fact cross join by your second fact table F2)
http://gerardnico.com/wiki/dat/obiee/bi_server/design/obiee_densification_design_preservation_dimension
Cheers
Nico

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

Summary Report with 4 Dimensions and 5 Facts

Hello OBIEE Czars:
I have a problem.
I am trying to make a summary report with 4 Dimensions and 5 Facts.
Out of that only 2 Dimensions are Confirmed.
Now when I try to bring in all the facts, I get view display error.
I searched forum for similar issues.
So I have tried following so far.
1) Add other dimensions as source and set level to Total for those dims.
- After doing this, I dont get view display error, but I get blank rows for couple of facts.
2) I am already aggregating all the measures.
Please help me out.
This forum has been very helpful so far.
Thanks.
~Vinay

Hi
This method seems fine until you run a request that includes a filter on an unconformed dimension.
The SQL itself should be quite straightforward (see below) but the BI Server instance does not seem to be joining this data correctly after posting the 2 separate queries to the database.
SELECT
x.dim1, x.dim2
x.fact1_agg_measure
y.fact2_agg_measure
FROM
SELECT
dim1, dim2
SUM(fact1.measure) fact1_agg_measure
FROM
dim1,
dim2, --UNCONFORMED+
fact1
WHERE
.... .... join fact1 to dimensions as normal
AND dim2 = 'BUSINESS_IDENTFIER'
GROUP BY
dim1, dim2
) x,
SELECT
dim1
SUM(fact2.measure) fact2_agg_measure
FROM
dim1,
fact2
WHERE
.... .... join fact2 to dimensions as normal
GROUP BY
dim1
) y
WHERE
x.dim1 = y.dim1
The result set returned in Answers is firstly a correctly aggregated record plus ALL rows from the second query above ??
Just wondering if anyone else has come across this issue?
cheers
Tony

How to link a fact table to one dimension many times

I have fact table which contains four date fields and I want to connect all of them to the Time dimension. I think I probably must split this fact table to multiple tables and then link them to dimensions. What is the right way to solve this kind of problem?
Example: Fact table: TimeIn, TimOut, TimeStart, TimeStop, InPlace, OutPlace, StartPlace, StopPlace, Speed, Weight, Width, Height .....
Thank you

Hello Kostis,
thank you for your answer. I don't fully understand you. Can you show me short example, please? I create alias table for time dimension on Physical Layer - original table is TimeDayDim and I create aliases TimeDayDim1, TimeDayDim2, TimeDayDim3, TimeDayDim4. Then I create foreign key Fact.Time1 -> TimeDayDim1, Fact.Time2 -> TimeDayDim2, Fact.Time3 -> TimeDayDim3, Fact.Time4 -> TimeDayDim4. And what now? Must I create these table api Bussines Model and create new time dimensions at bussiness model????
I need in Answers ONE Time dimension. I think I must split my fact table to four tables ... (time1, place1 ...) (time2, place2 ...) (time3 place3...) (time4 place4...) then link those tables to Time dimension (but I dont know where I can split those tables - on Physical Layer or on Bussines Layer).
I suppose that I will have in Answers one time dimension and four facts tables and I will be able to query them. (for example: Time.Days, Fact1.Place1, Fact3.Speed, Fact4.Count Criteria: Time.Year = 2008)
Best Regards Vlada

Linking 2 facts with common dimensions

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