Join fact tables with different grain without upsetting measures?
Say I am a business analyst at a university, and I have two analytical cubes available to me: an Enrollment Cube and an Admissions Cube. The Enrollment Cube has a grain of Student and Semester, whereas the Admission Cube has a grain of Student, Application and Semester (a potential student can have more than one application in a semester). Is there any way for the OLAP developer that makes these cubes to make it so that I can use both cubes' fact tables without messing up their corresponding measures, such that I can create such analyses as the following:
County
Semester
Acceptance Rate (Admission Fact)
Retention Rate (Enrollment Fact)
County A
1
30%
88%
2
60%
87%
3
42%
84%
County B
1
90%
100%
One suggestion is to create a view that joins the 2 fact tables and then create a cube with measures mapped to the view for analysis purposes. However, this would be using the measures of the new cube for the analysis.
Similar Messages
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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,
KateThanks 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 -
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. -
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 tables with different granularity
We currently have 3 dimensions (Site, Well, Date) and 2 fact tables (GasEngine, GasField), both having granularity of a day.
GasEngine is linked to Site and Date
GasField is linked to Site, Well and Date
We now have a requirement to make the GasEngine fact table have granularity of an hour but keep
GasField at a day.
We therefore must include a new Time dimension, which would only be linked to GasEngine.
Is it ok to have a DW with these two fact tables having different granularity?
And would we therefore require two separate cubes for querying this data?Hi Rajendra and Visakh16,
Based on your input provided to this thread, I would like to ask a question just to fine-tune my knowledge regarding data modelling. In Darren’s case I guess his date dimension only store dimension records up to day level granularity. Now the requirement
is to make the “GasEngine” fact table to hold data granularity of an hour.
Now based on Rajendra’s input
“Yes, you can have. but why you need new time dimension, I recommend, make GasEngine fact to
hour granularity.”
How Darren could display data for each hour without having a time dimension attached to GasEngine fact table? With the existing date dimension he ONLY can display the aggregated data with the minimum granularity of day level.
Now anyone can modify the date dimension to hold time records which will complicate the date dimension totally. Instead why Darren cannot have a separate time dimension which hold ONLY time related data and have a timekey in GasEngine fact table and relate
those tables using the time key? This way isn’t Darren’s data model become more readable and simplified? As we provide another way of slicing and dicing data by using a time dimension I do not think Darren’s cube becomes a complex STAR schema.
I could be totally wrong therefore for the sake of knowledge for Darren and me I am asking the question from both of you.
Best regards…
Chandima Lakmal Fonseka -
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 -
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 -
Using 2 fact tables with different granularity against calendar dimension
Hello gurus,
I have a requirement to provide a report to show the consumption of available capacity per month and also YTD.
I have two fact tables:
Fact table ‘Capacity’ with columns:
- Site_id
- Month_id
- Capacity
Ie.
001, 2010M01, 50
001, 2010M02, 50
001, 2010M12, 75
002, 2010M01, 60
002, 2010M02, 65
002, 2010M12, 80
Etc
Fact table ‘Consumption’ with columns
- Site_id
- Day_id
- Consumption
Ie
001, 20100101, 2
001, 20100102, 3
001, 20100131, 1
001, 20100201, 5
001, 20100212, 6
001, 20100228, 4
Etc
As can be see above, my ‘Capacity’ table contains monthly volumes, and the ‘Cunsumption’ table contains daily volumes.
My Calendar dimension is straightforward:
Year
Quarter_id
Month_id
Day_id
Ie
2010, 2010Q1, 2010M01, 20100101
2010, 2010Q1, 2010M01, 20100102
2010, 2010Q1, 2010M01, 20100103
2010, 2010Q1, 2010M01, 20100104
Etc
The MfgSite dimension is also simple:
Site_id
Site_name
Group
These are the steps I have taken sofar:
- Imported the four tables
- Created following joins:
MfgSite.Site_id = Capacity.Site_id
MfgSite.Site_id = Consumption.Site_id
Calendar.Month_id = Capacity.Month_id
Calendar.Day_id = Consumption.Day_id
- Created Business Model Diagram in BMM
- Created Calendar hierachy:
Year, Quarter, Month, Day
- Created MfgSite hierarchy:
Group, SiteName
- Setup Logical Table Source / Content settings as follows:
Fact table Capacity:
Dimension MfgSite: Logical Level = Site
Dimension Calendar: Logical Level = Month
Fact table Consumption:
Dimension MfgSite: Logical Level = Site
Dimension Calendar: Logical Level = Day
- Set Default Aggregation Rule to Sum on Logical Columns:
Capacity.Capacity
Consumption.Consumption
- Created following YTD Logical Columns:
YTDCapacity = TODATE(Capacity.Capacity, Calendar.Year)
YTDConsumption = TODATE(Consumption.Consumption, Calendar.Year)
- Created Presentaion layer
I then built a few reports to test it out and found that I have an issue with the Capacity object: When I build a simple report to show capacity per month:
SiteName, Month, Capacity
the capacity for each month is multiplied by the number of calendardays in that months, so I get
Site Month Capacity
001 2010M01 1550 (= 31 x 50)
001 2010M02 1400 (= 28 x 50)
Etc
In addition, when I add YTDCapacity to my report, the report fails with the following message:
Unable to navigate requested expression: ToDate(Capacity:[DAggr(Capacity.Capacity by [ Calendar.Year, Calendar.Month_id, MfgSite.Site_id, MfgSite.SiteName] )], [Level Year]). Please fix the metadata consistency warnings. (HY000)
Did I miss any steps? Any help is greatly appreciated!
Thanks!
Randallhi in the capacity fact table remove the level set for the calendar dim and see.
-
How to join 2 tables with unequal rows without resulting in a cartesian join
Hello,
This is the first time I have ever posted in any forum so please tell me if I should be doing this better.
Basically I have 2 tables with an unequal number of rows. For demonstration purposes, assume these are my 2 tables:
Table 1:
BaseKey
Letters
A
A
A
B
A
C
B
A
B
B
Table 2:
BaseKey
Numbers
A
1
A
2
B
1
B
2
B
3
I need to join them so that the data would appear like this
BaseKey
Letters
Numbers
A
A
1
A
B
2
A
C
null
B
A
1
B
B
2
B
null
3
Does anyone have any ideas how to do this using T-SQL without creating a cartesian join of 12 rows?
Thanks.>> This is the first time I have ever posted in any forum so please tell me if I should be doing this better. <<
Please post DDL, so that people do not have to guess what the keys, constraints, Declarative Referential Integrity, data types, etc. in your schema are. Learn to follow ISO-11179 data element naming conventions and formatting rules. Temporal data should
use ISO-8601 formats. Code should be in Standard SQL as much as possible and not local dialect.
This is minimal polite behavior on SQL forums. What you did post is useless! Can you program from it? Neither can we. And we have to do all the extra typing for you.
CREATE TABLE Foo
(base_something CHAR(1) NOT NULL,
something_letter CHAR(1) NOT NULL,
PRIMARY KEY (base_something, something_letter));
INSERT INTO Foo
VALUES ('A', 'A'),
('A', 'B'),
('A', 'C'),
('B', 'A'),
('B', 'B');
CREATE TABLE Bar
(CHAR(1) NOT NULL,
something_digit CHAR(1) NOT NULL,
PRIMARY KEY (base_something, something_digit));
INSERT INTO Foo
VALUES ('A', '1'),
('A', '2'),
('B', '1'),
('B', '2'),
('B', '3');
>> I need to join them so that the data would appear like this
base_something Letters Numbers <<
This looks like you are taking two decks of punch cards and merging them together, without any logical rules, just physical position in their decks relative to the base_something groups.
WITH Foo_Deck
AS
(SELECT base_something, something_letter,
ROW_NUMBER()
OVER (PARTITION BY base_something
ORDER BY something_letter) AS card),
Bar_Deck
AS
(SELECT base_something, something_digit,
ROW_NUMBER()
OVER (PARTITION BY base_something
ORDER BY something_digit) AS card),
SELECT F.base_something, F.something_digit, B.something_letter
FROM Foo_Deck AS F
LEFT OUTER JOIN
Bar_Deck AS B
ON B.base_something = F.base_something
AND B.card = F.card;
--CELKO-- Books in Celko Series for Morgan-Kaufmann Publishing: Analytics and OLAP in SQL / Data and Databases: Concepts in Practice Data / Measurements and Standards in SQL SQL for Smarties / SQL Programming Style / SQL Puzzles and Answers / Thinking
in Sets / Trees and Hierarchies in SQL -
Fact table with different dates
Hello,
In my fact table I have several date columns (order date, payment date, ....) and I have only one time table in my physical model.
For example this model
Fact table
order day
payment day
Timetable
day - pk
I want to create 2 fks in order to have time analyse with order date and payment date
FK1 : fact_table.order_day and timetable.day
FK2 : fact_table.payment_day and timetable.day
validating the model, OBI tells me that i cant' t have various joins between 2 tables
Anyone know how to solve this ? (I think it is a quite common problem)
Thanks in advanceCreate an alias for your dimension Timetable and then join that with your fact table. So basically you would have 2 dimensions, one joining with order day the other joining with payment day.
Thanks,
Venkat
http://oraclebizint.wordpress.com -
Joining two tables with different DB
Hi
We have 2 sources DB2 and Oracle.
In DB2 we have two tables which stores.
Tbl1
Case_no Information1 Information2 Information3
11112 sddf asd null null
11113 asd asd null null
Tbl2
Inf Info1 Code Info3
Xedy Asdf 111 afder
Mad Tag 123 top
The above tables are complex join with this condition
Tbl1.case_no=Tbl1.case_no.
Oracle tbl
Code Code_desc
111 Very good
123 bad
My requirement is to join the tbl2 with Oracle tbl. Based on the codes in DB2 table I should display the Code_desc in my reports. Like this
Case_no Code Code_desc
11112 111 Very good
11113 123 bad
But I am getting the Cartesian result.
Case_no Code Code_desc
11112 111 Very good
11112 123 bad
11113 111 Very good
11113 123 bad
Please help to resolve.
Regards
MDSelect Oracletbl and tbl2, right click on them open physical diagram, selected objects. In the physical diagram page Create a join between Oracletbl and tbl2 with the condition code=code.
In business model create a complex join between these two. Now reload metadata/restart services check output.
Let me know if this does not work you. -
Joining Facts With Different Grains to NonConfirming Dimensions - Mystery
Hi ,
Taxonomy Used is - CD stands for Confirmed Dimension && NCD stands for Non Confirmed Dimension.
I have 3 Dimensions (CD1,NCD2,NCD3) and 2 facts (F1 & F2).
==> Fact F1 can be joined to only CD1 and NCD2 dimensions. Grain of Fact F1 is same as CD1 i.e., Nbr of records matches 1 to 1 between CD1 and F1F2
==> Fact F2 can be joined to only CD1 and NCD3 dimensions. Grain of Fact F2 is CD1 & NCD3. There could be multiple records for same value of CD1 within Fact F2, and similarly there could be multiple records for same value of NCD3. But there will always be just 1 and only 1 record for combination of CD1 and NCD3.
Report Requirements:-
1) Get few Metrics from F2 and few from F1 while applying a filter on NCD2. so below columns are needed :-
Dimension Column from NCD2 || Metric from Fact1 || Metric from Fact2
So need to understand how to enforce the relationship between Fact F2 and Dimension NCD2
2) Get few Metrics from F2 and few from F1 while applying a filter on NCD2 and also Display NCD3. so below columns are needed :-
Dimension Column from NCD2 || Dimension Column from NCD3 ||Metric from Fact1 || Metric from Fact2
==> In above case it is perfectly acceptable if Metric from Fact 1 repeats again as Fact1 is at higher Grain as compare to Fact2.
Edited by: user10799880 on Apr 15, 2013 9:37 PMHi,
refer to this
http://108obiee.blogspot.com/2009/08/joining-two-fact-tables-with-different.html
mark helps
thanks -
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 ! -
Joining Facts with Different Grains
Hello
We have a requirement where we have two facts with different grains
DEPT_FACT - Contains (Dept_Id, Dept_Name, Revenue)
EMP_FACT - Contains (Emp_Id, Dept_Name, Is_Current_Employee)
Here is some sample data
DEPT_FACT
========
1 Sales_Dept 100,000
2 Manufacturing_Dept 200,000
EMP_FACT
========
100 Sales_Dept Y
200 Sales_Dept Y
300 Sales_Dept N
400 Manufacturing_Dept N
500 Manufacturing_Dept Y
600 Manufacturing_Dept N
Our requirement is to create an OBIEE report that shows the *"Revenue/ Number of current employees in department BY Department"*
The above example must show
Sales_Dept => $50,000 (100,000 / 2 current employees)
Sales_Dept => $200,000 (200,000 / 1 current employee)
Any suggestions on how this can be done ?For me,
DEPT_FACT is not a fact. It's a dimension table because you have a one-to-many relationship and you have a measure in the dimension table (it's an aggregated measure).
And EMP_FACT is also not a fact because you don't have any measure on it.
But if we say that EMP_FACT is a fact. DEPT_FACT is an aggregated table from EMP_FACT.
I will :
* create a logical dimension for the employee with three levels (all, departement and detail)
* create a logical fact table with :
- one logical column for the revenue in the level all departement
- one logical column for the employee
and two physical source :
* DEPT_FACT with the departement level
* EMP_FACT with the level to detail
Success
Nico -
Relating facts with different grains
I'm having an issue designing a cube/star schema where I need to relate 2 fact tables that are at a different grain.
I currently have a star with 1 fact table (Insurance Premium) and 3 dimensions (Date, Account, Policy). The fact table has 1 row for each policy within each account for every quarter (quarterly snapshot). The measure is Premium.
We need to enhance this star with a new fact table that stores Lost Accounts for each quarter. The difference with this data is that we only get it at the Account Level. So the Fact table will have 1 row for each lost account per quarter. The
measure is Lost Premium.
I created the Lost Business Fact table which relates to the same Date and Account dimension as the Insurance Premium Fact table. In the cube, i created a new measure group for the Lost Premium fact table and related it to the same Date and Account
dimensions.
the 2 issues that I am having are:
1. In the Policy Dimension table, there is a field called AccountBroker, which stores the Broker for the account. So if the account has 5 policies, this table will have 5 rows and the AccountBroker field will be the same for each row. The
end users want to be able to use this field (AccountBroker) in the Lost Premium Fact table so that they can slice and dice the Lost Premium by Account Broker. The issue is that I'm not sure how to relate the Lost Premium Fact to the Policy Dimension
since the Lost Premium Fact is at Account level and the Policy Dimension is at Policy Level.
2. The other issue is that when we receive the Lost Business File for each quarter, the account may not be present in the Premium Fact because it was lost. So for example, for Q1 2014, account 1234 was lost and we receive a record in the Lost
Business File with Account 1234 as being lost and it gets inserted into the Lost Premium Fact. However, when we get the file that loads the Insurance Premium Fact for Q1 2014, this account is not present because it was lost in that quarter, so there
is no way to link the records. My first thought was to maybe take the records from the previous quarter (Q4 2012) and insert those records for Q1 2014 into the Insurance Premium Fact with 0 premium so that they exist and then there will be a match, but
not sure if there is a better design.
any ideas would be appreciated.
thanks
ScottFor me,
DEPT_FACT is not a fact. It's a dimension table because you have a one-to-many relationship and you have a measure in the dimension table (it's an aggregated measure).
And EMP_FACT is also not a fact because you don't have any measure on it.
But if we say that EMP_FACT is a fact. DEPT_FACT is an aggregated table from EMP_FACT.
I will :
* create a logical dimension for the employee with three levels (all, departement and detail)
* create a logical fact table with :
- one logical column for the revenue in the level all departement
- one logical column for the employee
and two physical source :
* DEPT_FACT with the departement level
* EMP_FACT with the level to detail
Success
Nico
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