Are fact tables and cubes same in OWB?

Dear all
A simple question. How can I create a star schema (that is, with a fact table and dimensions) using OWB?
OWB has options to create cubes, but as per my understanding a cube is not a fact table.
Cube contains pre-computed data where as fact table contains normal data with references to dimensions.
Please correct me if I am wrong.
thanks in advance

These are just different levels of abstraction.
"Cube" is the highest level of abstraction referring to the overall package of data.
"Star schema" is how cubes are modelled showing the relationships from a fact entity to the dimension entities.
Relational and OLAP are different methods of physical implementation.
In OWB, to promote sharing of dimensions across cubes to avoid inconsistency the idea is you define and build the dimensions independently. Then you define the "cubes" as measures and references to the dimensions. When you build the "cube" you pass in business identifiers from the source data which OWB will use to link the measures to the applicable dimension data. Due to the wonders of inner joins anyone reading the "cube" will only see dimension data related to the data in that cube!
Using OWB you do not need to be concerned with the physical implementation when you use the dimension and cube operators as those operators know what to do.

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Merging Multiple fact tables and creating a BIA target

Hi Folks
We are using Dataservices with BIA.
We want to merge mutliple fact table and create a sinvglc cube on BIA.
when we tried to do that we get a error message that we cannot merge multiple fact tables.
any pointers ?
Poonam

You could have the cubes individually on the BIA and then have a multiprovider which you can use..?
or create separate universes on the cubes and then merge the universes in BO and then you could hit the BIA for the same..?

How to handle 3 different fact tables and measures within a DAX query?

I am writing a DAX query in DAX studio in Excel against a tabular model that has 4 different Fact tables, but they share the same dimensions. (There's some long story I can't get into here, but unfortunately this is the structure) I want to
include measures from the 4 fact tables, summarize by the dimensions in a single query output that can be used for a pivot table. So far I have something like this:
EVALUATE
FILTER
    SUMMARIZE
        FactTable1,
        DimensionTable1[Value],        DimensionTable2[Value],
        DimensionTable3[Value],
        Dimensiontable4[Value],
        'dimDateTime'[Month PST],
        DimDateTIme[FiscalYear PST],
        "Measure Score",
        FactTable1[Measure 1],
        "Measure Score 2",
        FactTable1[Measure 2],
    ,Company[CompanyName]="Company ABC"
What I want to do is summarize the 3 fact tables by the same dimensions, but I am not sure how to do that within a DAX query. I am getting an error if I try to include another table statement in the original SUMMARIZE function, even though the FACTS
do share the same dimension. Is there an easy way to do this?

You can use ADDCOLUMNS to add the data from other tables, but you need to use within the SUMMARIZE the fact table that determines the cardinality of the output. If you are not sure (e.g. you project cost and revenues from two fact tables by month and there
could me months with cost and no revenues, but also months with revenues and no costs), then you should use CROSSJOIN and then FILTER.
You query might be written as (please note CALCULATETABLE instead of FILTER to improve performance):
EVALUATE
CALCULATETABLE (
    ADDCOLUMNS (
        SUMMARIZE (
            FactTable1,
            DimensionTable1[Value],
            DimensionTable2[Value],
            DimensionTable3[Value],
            Dimensiontable4[Value],
            'dimDateTime'[Month PST],
            DimDateTIme[FiscalYear PST]
        "Measure Score", FactTable1[Measure 1],
        "Measure Score 2", FactTable1[Measure 2]
    Company[CompanyName] = "Company ABC"
Marco Russo http://www.sqlbi.com http://www.powerpivotworkshop.com http://sqlblog.com/blogs/marco_russo

Multiple fact tables and dimensions

I have two fact tables actual sales and planned sales and 8 dimension tables, using a star schema. I want to query on the two fact tables with two dimensions, product and time. When I create the report in discoverer i bring in the sales from actuals and then the product_desc and month_desc. Then I bring in the measure from the second fact table and a join window pops up asking which join to use. If I choose the join to the time dimension then I get no data for the second fact table and correct data for the first fact table. If I choose the product dimension then I get correct data for the first fact table and grossly incorrect data for the second fact table.
How can I stop this from happening?
Nick

Nick,
I hope you solved your reporting issue and can share the solution with me. I am encountering the same problem. I have used Oracle Warehouse Builder 10Gr2 to design and deploy a pretty simple ROLAP data mart. We are using Discoverer Plus for OLAP as our reporting tool. We have 5 dimension tables using a star schema and have 3 fact tables, when I create the worksheet I bring in our sales measure from our sales item table and then Store_Name from my Stores Dimension and then week-ending from my time dimension, everything looks good at the stage. Then I bring in a measure from our advertising cost table and a join window pops up asking which join to use, if I choose either the Store or the Time dimension I get correct data for the first fact table (sales) and grossly incorrect data for the ad cost from the second fact table (advertsing costs)...... any help would be appreciated
monalisa

How to combine multiple fact tables and dimensions in one worksheet?

Hello Forum,
I am encountering a reporting problem when trying to create a worksheet that uses more than one cube/fact table and common dimensions. I have used Oracle Warehouse Builder 10Gr2 to design and deploy a pretty simple ROLAP data mart. We are using Discoverer Plus for OLAP as our reporting tool. We have 5 dimension tables using a star schema and 3 fact tables, when I create the worksheet I bring in our sales measure from our sales item table and then Store_Name from my Stores Dimension and then day from my time dimension, everything looks good at the stage, we're just trying to get a sum of all sales for that store on that day. Then I bring in a measure from our advertising cost table and a join window pops up asking which join to use, if I choose either the Store or the Time dimension I get correct data for the first fact table (sales) and grossly incorrect data for the ad cost measure from the second fact table (advertsing costs)...... any help would be appreciated

You have encountered one of the key limitations of Discoverer... which I complained about to the Discoverer product manager at OpenWorld in 2001....
Anyhow, to get around this, you are going to have to deal with it either in the database, (views, materialized views, tables), or within the admin tool by creating a custom folder.
Discoverer also calls this the "fan trap", but never really had a solution to the problem. [The solution only worked is you joined to one and only one dimension!]
What you want (using Sales_Fact and Inventory_Fact as an example) is to join Sales to Time, Store, and Product, and save that result. Then join Inventory to Time, Store, and Product, save that result, then do a double outer join between the two intermediate temporary tables in order to calculate something useful like inventory turns by store and product line.
This is also known a "multipass SQL", and is supported by some (but not many) other tools.
So, to accomplish this with Discoverer, you'll either need to create a view, or table, or materialized view that has already put Sales and Inventory into a single (virtual?) fact table. Alternatively you can write the SQL for how to do this linkage (don't forget to handle missing data), and use the Discoverer admin tool to create a custom folder that uses your SQL.
Hope this helps!

Resolving loops in a star schema with 5 fact tables and 6 dimension tables

Hello
I have a star schema, ie 5 FACT tables and 7 dimension tables, All fact tables share the same dimension tables, some FACT tables share 3 dimesnsions, while other share 5 dimensions.
I did adopt the best practices, and as recommended in the book, I tried to resolve them using Context, as it is the recommended option to Alias in a star schema setting. The contexts are resolved, but I still have loops. I also cleared the Multiple SQL Statement for each context option, but no luck. I need to get this resoved ASAP

Hi Patil,
It is not clear what exactly is the problem. As a starting point you could set the context up so that it only covers the joins from fact to dimension.
Fact A, joins Dim 1, Dim 2, Dim 3, and Dim 4
Fact B, joins Dim 1, Dim 2, Dim 3, Dim 4 and Dim 5
Fact C, joins Dim 1, Dim 2, Dim 3, Dim 4 and Dim 6
Fact D, joins Dim 1, Dim 2, Dim 3, Dim 4 and Dim 7
Fact E, joins Dim 1, Dim 2, Dim 4 and Dim 6
If each of these are contexts are done and just cover the joins from fact to dim then you should be not get loops.
If you could lay out your joins like above then it may be possible to specify the contexts/aliases that should work.
Regards
Alan

Reg: Fact table and Dimension table in Data Warehousing -

Hi Experts,
I'm not exactly getting the difference between the criteria which decide how to create a Fact table and Dimension table.
This link http://stackoverflow.com/questions/9362854/database-fact-table-and-dimension-table states :
Fact table contains data that can be aggregate.
Measures are aggregated data expressions (e. Sum of costs, Count of calls, ...)
Dimension contains data that is use to generate groups and filters.
This's fine but how does one decide which columns to consider for Fact table and which columns for Dimension table?
Any help is much appreciated.
Pardon me if this's not the correct place for this question. My first question in the new forum.
Thanks and Regards,
Ranit Biswas

ranitB wrote:
But my main doubt was - what is the criteria to differentiate between columns for Fact tables and Dimension tables? How can one decide upon the design?
Columns of a fact table will often be 'scalar' attributes of the 'fact' data item. A dimension table will often be 'compound' attributes of a 'fact'.
Consider employee information. The EMPLOYEE table can be a fact table. It might have scalar attribute columns such as: DATE_HIRED, STATUS, EMPLOYEE_ID, and so on.
Other related information that can't be specified as a single attribute value would often be stored in a 'dimension' table: ADDRESS, PHONE_NUMBER.
Each address requires several columns to define it: ADDRESS1, ADDRESS2, CITY, STATE, ZIP, COUNTRY. And an employee might have several addresses: WORK_ADDRESS, HOME_ADDRESS. That address info would be stored in a 'dimension' table and only the primary key value of the address record would be stored in the EMPLOYEE 'fact' table.
Same with PHONE_NUMBER. Several columns are required to define a phone number and each employee might have several of them. The dimension tables are used to help 'normalize' the data in the employee 'fact' table.
And that EMPLOYEE table might also be a DIMENSION table for other FACT tables. A DEVELOPER table might have an EMPLOYEE_ID column with a value that points to a 'dimension' row in the EMPLOYEE dimension table.

2 Fact Tables with a same content level

Hi,
I have 2 fact tables F1,F2 joined to the same 4 dimensions D1,D2,D3,D4.The detail level # of elements multiplied for all the dimensions D1,D2,D3,D4 are the same for both dimension.I even set the content level for the 2 fact tables and the content filter is the same in both fact tables F1.Column1=0 in F1 fact table and F2.Column1=0 in F2 fact table.So how does OBIEE decide which fact table to select in this scenario.
I went through the below blog but could not get much information
http://obiee-blog.info/administration-tool/what-rule-is-followed-when-several-fact-are-at-the-same-content-level/
I appreciate if anyone can guide me with the right answers.

How many records retrieving when joining F1 & F2 with dimension ? if the f1 and d1 has 200 records and f2 and d1 is retriving 100 records it chooses shortest path.
thanks,
Saichand

What is FACT table and FLAT table?

Hello,
         Kindly tell me what is mean by FACT table and FLAT table and how it is use in the BI system ?also tell me can i see these table in the system ?if yes then please tell me the procedure to see the content of the FACT and FLAT table.   And also tell me about the SID table and how to see it.

Cube consists of Fact tables and Dimension tables.
The structure of these tables are "Flat".
Cube consists of two factables... 'F' - Fact table and 'E' - Fact table.
The naming convention will be..
/BIC/F<..Cube name..>   for F Fact table
/BIC/E<..Cube name..>   for E Fact table
Eg: for cube "EMPLOYEE" the names are..
/BIC/FEMPLOYEE
/BIC/EEMPLOYEE
The dimention tables have naming convention..
/BIC/D....
You can check these tables in SE11 or you can use the transaction LISTSCHEMA and then provide the Cube name.
SID's tables are used to link the master data with the dimention tables.

Ratio between Fact table and Dimention table for a Infocube

Hi All,
How can we reduce the Ratio between Fact table and Dimention table for a Infocube below 20%.??
please give suggestions

Hi
Reduce Ratio??
The Ratios are dependent on the Fact Table, and the Dimension table that is modeled for your Cube.
You cannot change ratio individually, but can set the Line Item Dimension , provided you have only one char object is taking much space and bulky with much percentage, based on your requirement. You can always use fine tuning objects.
Please be more specific while posting, to get right help from sdn.
Hope it helps

Fact Table and Dimension Tables

Hi Experts, I'm creating custom InfoCubes for data coming from non-SAP source systems. I have two InfoCubes. Tha data is coming from like 10 tables. I have 10 DataSources created fo this and the data will be consolidated in Standard DSO before it will flow into 2 InfoCubes.
Now client wants to know before how much data will be there in InfoCubes in Fact table nad Dimension tables in both the InfoCubes. I have the total size of all the 10 tables from the sources given to me by the DBA. I wan not sure how I can convert that info for Fact table and Dimension table as I have not yet created these Infocubes.
Please help me with this on how I should address this.

hi,
The exact data will be hard to give however you can reach at a round figure in your case.
You are consolidating the data from the tables that means that there is relation between the tables. Arrive at a rough figure based on the relation and the activity you are performing while consolidating the data of the tables.
For example, let us say we want to combine data for sales order and deliveries in a DSO.
Let Sales order has 1000 records and Delivery has 2000 records. Both the tables have a common link (Sales Order).In DSO you are combining the data that means the data will be at the most granular level consist of Delivery data, so the maximum no of records which the consolidated DSO can have is 2000.
regards,
Arvind.

Join multiple fact tables and dimensions and use all tables in report issue

Hi,
I have a report requirements and need to use multiple fact tables and unconformed dimensions as described below
Fact table: F1,F2,F3
Dimensions tables: D1.....D9
F1:(joined to) D1,D2,D3,D4
F2::(joined to)D1,D2,D5,D6
F3::(joined to)D1,D2,D7,D8
D7::(joined to)D9,D8 (dimension D7 joined to two other dimensions D9 and D8
I'm trying to use columns from almost all the fact and dimension tables but getting "Unable to navigate requested expression. Please fix the metadata consistency warnings."
Repository is consistent and no errors and warnings.
How can I configure the repository to develop reports using all fact tables and dimensions?
Appreciate for your help.
Thanks
Jay.
Edited by: Jay on Feb 9, 2012 4:14 PM

So you want me to convert snowflake schema to star. does it solve my problem? individual star queries are working find but when I query multiple stars together getting inconsistency errors. I removed content tables dim level totals for unconformed dimensions in logical fact LTS and set level for measures at total level for unconformed dimensions. it is still in progress and need to test.
Thanks
Jay.

Multiple 'logical joins' between a fact table and one dimension table

It appears that one cannot create multiple ‘logical joins’ between a fact table and one dimension table in OBIEE using the Oracle BI Administration Tool. For example, considering a Business Model with a dimension table TIMES and a fact table FACT containing START_TIME and END_TIME, we would like to create separate logical joins from FACT to TIMES for the START_TIMEs and END_TIMEs? Obviously, the underlying foreign keys can be created, but as far as I can tell the Oracle BI Administration Tool doesn’t support this. The workaround would be to replicate the TIMES table, but that’s ugly.
I seek an alternative approach.

Try this. Create an two aliases for the TIMES dimension (Start & End) in the Physical Layer and then remove foreign key to the "Parent" Times dimension. Create the Foreign Key in the Physical Layer to the new aliases and then create the complex joins in the BMM Layer to the new aliases as well. This will allow you to present both dates within the same table in the Presentation Layer. Not the most elegant solution but it works.

Fact table and dimension table

what is the difference b/w fact table and dimension table

A fact table contains numeric values and also contain composite key(i.e collection of foreign key) e.g.. sales and profit. Typically has two types of columns: those that contain facts and those that are foreign keys to dimension tables.
Dimension tables, also known as lookup or reference tables, contain the relatively static data in the warehouse. It contains character values E.g Customer_name,Customer_city.
Dimension tables store the information you normally use to contain queries. Dimension tables are usually textual and descriptive and you can use them as the row headers of the result set.
Rachna

Sizeof fact table and dimension table

Hi Experts ,
Can you tell me how to measure the size of dimension table and fact tables and how to find the ratio of size of dimension table to the size of fact table.
Thanks in advance,
Thanks and Regards
Ram Kommineni

Hi,
The ratio of size of fact table to dimension table is ideally should be 10:1. That means the size of the dimension tables should be 10% of the size of the fact table. This serves better in terms of performance.
Whenever you load any cube, you can easily find out the number of records in fact table (E and F table) and the dimension tables. Based on that statistics you can determine the ratio of size in fact and dimension tables.
Hope this info helps you.
Regards,
Yogesh.

Are fact tables and cubes same in OWB?

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