Filtering on a dimension table

Hi all,
I am trying to bring in a field from a dimension table-to be used in my mapping. This is based on a condition.(All attributes belong to the same level in the dimension).
I brought in the dimension using the 'dimension' operator and tried to 'filter' on the condition and then connect the field from source to target. I get this error:
API 8003: Connection target attribute group is already connected to an incompatible source. Use a joiner or set operator to join the upstream data first before connecting it into this operator.
Any suggestions?
Thanks.

Hi,
I am already doing that. I connected the dimension(through a filter) to a lookup operator, and then to the target table.
I get this error when I validate:
VLD-1104: Attributes flowing into DEDUP_SRC_0:INOUTGRP1 have different data sources.
Any suggestions?
Thanks,

Similar Messages

How to Maintain Surrogate Key Mapping (cross-reference) for Dimension Tables

Hi,
What would be the best approach on ODI to implement the Surrogate Key Mapping Table on the STG layer according to Kimball's technique:
"Surrogate key mapping tables are designed to map natural keys from the disparate source systems to their master data warehouse surrogate key. Mapping tables are an efficient way to maintain surrogate keys in your data warehouse. These compact tables are designed for high-speed processing. Mapping tables contain only the most current value of a surrogate key— used to populate a dimension—and the natural key from the source system. Since the same dimension can have many sources, a mapping table contains a natural key column for each of its sources.
Mapping tables can be equally effective if they are stored in a database or on the file system. The advantage of using a database for mapping tables is that you can utilize the database sequence generator to create new surrogate keys. And also, when indexed properly, mapping tables in a database are very efficient during key value lookups."
We have a requirement to implement cross-reference mapping tables with Natural and Surrogate Keys for each dimension table. These mappings tables will be populated automatically (only inserts) during the E-LT execution, right after inserting into the dimension table.
Someone have any idea on how to implement this on ODI?
Thanks,
Danilo

Hi,
first of all please avoid bolding something. After this according Kimball (if i remember well) is a 1:1 mapping, so no-surrogate key.
After that personally you could use Lookup Table
http://www.odigurus.com/2012/02/lookup-transformation-using-odi.html
or make a simple outer join filtering by your "Active_Flag" column (remember that this filter need to be inside your outer join).
Let us know
Francesco

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.

Fact and dimension table partition

My team is implementing new data-warehouse. I would like to know that when should we plan to do partition of fact and dimension table, before data comes in or after?

Hi,
It is recommended to partition Fact table (Where we will have huge data). Automate the partition so that each day it will create a new partition to hold latest data (Split the previous partition into 2). Best practice is to create partition on transaction
timestamps so load the incremental data into a empty table called (Table_IN) and then Switch that data into main table (Table). Make sure your tables (Table and Table_IN) should be on one file group.
Refer below content for detailed info
Designing and Administrating Partitions in SQL Server 2012
A popular method of better managing large and active tables and indexes is the use of partitioning. Partitioning is a feature for segregating I/O workload within
SQL Server database so that I/O can be better balanced against available I/O subsystems while providing better user response time, lower I/O latency, and faster backups and recovery. By partitioning tables and indexes across multiple filegroups, data retrieval
and management is much quicker because only subsets of the data are used, meanwhile ensuring that the integrity of the database as a whole remains intact.
Tip
Partitioning is typically used for administrative or certain I/O performance scenarios. However, partitioning can also speed up some queries by enabling
lock escalation to a single partition, rather than to an entire table. You must allow lock escalation to move up to the partition level by setting it with either the Lock Escalation option of Database Options page in SSMS or by using the LOCK_ESCALATION option
of the ALTER TABLE statement.
After a table or index is partitioned, data is stored horizontally across multiple filegroups, so groups of data are mapped to individual partitions. Typical
scenarios for partitioning include large tables that become very difficult to manage, tables that are suffering performance degradation because of excessive I/O or blocking locks, table-centric maintenance processes that exceed the available time for maintenance,
and moving historical data from the active portion of a table to a partition with less activity.
Partitioning tables and indexes warrants a bit of planning before putting them into production. The usual approach to partitioning a table or index follows these
steps:
1. Create
the filegroup(s) and file(s) used to hold the partitions defined by the partitioning scheme.
2. Create
a partition function to map the rows of the table or index to specific partitions based on the values in a specified column. A very common partitioning function is based on the creation date of the record.
3. Create
a partitioning scheme to map the partitions of the partitioned table to the specified filegroup(s) and, thereby, to specific locations on the Windows file system.
4. Create
the table or index (or ALTER an existing table or index) by specifying the partition scheme as the storage location for the partitioned object.
Although Transact-SQL commands are available to perform every step described earlier, the Create Partition Wizard makes the entire process quick and easy through
an intuitive point-and-click interface. The next section provides an overview of using the Create Partition Wizard in SQL Server 2012, and an example later in this section shows the Transact-SQL commands.
Leveraging the Create Partition Wizard to Create Table and Index Partitions
The Create Partition Wizard can be used to divide data in large tables across multiple filegroups to increase performance and can be invoked by right-clicking
any table or index, selecting Storage, and then selecting Create Partition. The first step is to identify which columns to partition by reviewing all the columns available in the Available Partitioning Columns section located on the Select a Partitioning Column
dialog box, as displayed in Figure 3.13. This screen also includes additional options such as the following:
Figure 3.13. Selecting a partitioning column.
The next screen is called Select a Partition Function. This page is used for specifying the partition function where the data will be partitioned. The options
include using an existing partition or creating a new partition. The subsequent page is called New Partition Scheme. Here a DBA will conduct a mapping of the rows selected of tables being partitioned to a desired filegroup. Either a new partition scheme should
be used or a new one needs to be created. The final screen is used for doing the actual mapping. On the Map Partitions page, specify the partitions to be used for each partition and then enter a range for the values of the partitions. The
ranges and settings on the grid include the following:
Note
By opening the Set Boundary Values dialog box, a DBA can set boundary values based on dates (for example, partition everything in a column after a specific
date). The data types are based on dates.
Designing table and index partitions is a DBA task that typically requires a joint effort with the database development team. The DBA must have a strong understanding
of the database, tables, and columns to make the correct choices for partitioning. For more information on partitioning, review Books Online.
Enhancements to Partitioning in SQL Server 2012
SQL Server 2012 now supports as many as 15,000 partitions. When using more than 1,000 partitions, Microsoft recommends that the instance of SQL Server have at
least 16Gb of available memory. This recommendation particularly applies to partitioned indexes, especially those that are not aligned with the base table or with the clustered index of the table. Other Data Manipulation Language statements (DML) and Data
Definition Language statements (DDL) may also run short of memory when processing on a large number of partitions.
Certain DBCC commands may take longer to execute when processing a large number of partitions. On the other hand, a few DBCC commands can be scoped to the partition
level and, if so, can be used to perform their function on a subset of data in the partitioned table.
Queries may also benefit from a new query engine enhancement called partition elimination. SQL Server uses partition enhancement automatically if it is available.
Here’s how it works. Assume a table has four partitions, with all the data for customers whose names begin with R, S, or T in the third partition. If a query’s WHERE clause
filters on customer name looking for ‘System%’, the query engine knows that it needs only to partition three to answer
the request. Thus, it might greatly reduce I/O for that query. On the other hand, some queries might take longer if there are more than 1,000 partitions and the query is not able to perform partition elimination.
Finally, SQL Server 2012 introduces some changes and improvements to the algorithms used to calculate partitioned index statistics. Primarily, SQL Server 2012
samples rows in a partitioned index when it is created or rebuilt, rather than scanning all available rows. This may sometimes result in somewhat different query behavior compared to the same queries running on SQL Server 2012.
Administrating Data Using Partition Switching
Partitioning is useful to access and manage a subset of data while losing none of the integrity of the entire data set. There is one limitation, though. When
a partition is created on an existing table, new data is added to a specific partition or to the default partition if none is specified. That means the default partition might grow unwieldy if it is left unmanaged. (This concept is similar to how a clustered
index needs to be rebuilt from time to time to reestablish its fill factor setting.)
Switching partitions is a fast operation because no physical movement of data takes place. Instead, only the metadata pointers to the physical data are altered.
You can alter partitions using SQL Server Management Studio or with the ALTER TABLE...SWITCH
Transact-SQL statement. Both options enable you to ensure partitions are
well maintained. For example, you can transfer subsets of data between partitions, move tables between partitions, or combine partitions together. Because the ALTER TABLE...SWITCH statement
does not actually move the data, a few prerequisites must be in place:
• Partitions must use the same column when switching between two partitions.
• The source and target table must exist prior to the switch and must be on the same filegroup, along with their corresponding indexes,
index partitions, and indexed view partitions.
• The target partition must exist prior to the switch, and it must be empty, whether adding a table to an existing partitioned table
or moving a partition from one table to another. The same holds true when moving a partitioned table to a nonpartitioned table structure.
• The source and target tables must have the same columns in identical order with the same names, data types, and data type attributes
(length, precision, scale, and nullability). Computed columns must have identical syntax, as well as primary key constraints. The tables must also have the same settings for ANSI_NULLS and QUOTED_IDENTIFIER properties.
Clustered and nonclustered indexes must be identical. ROWGUID properties
and XML schemas must match. Finally, settings for in-row data storage must also be the same.
• The source and target tables must have matching nullability on the partitioning column. Although both NULL and NOT
NULL are supported, NOT
NULL is strongly recommended.
Likewise, the ALTER TABLE...SWITCH statement
will not work under certain circumstances:
• Full-text indexes, XML indexes, and old-fashioned SQL Server rules are not allowed (though CHECK constraints
are allowed).
• Tables in a merge replication scheme are not allowed. Tables in a transactional replication scheme are allowed with special caveats.
Triggers are allowed on tables but must not fire during the switch.
• Indexes on the source and target table must reside on the same partition as the tables themselves.
• Indexed views make partition switching difficult and have a lot of extra rules about how and when they can be switched. Refer to
the SQL Server Books Online if you want to perform partition switching on tables containing indexed views.
• Referential integrity can impact the use of partition switching. First, foreign keys on other tables cannot reference the source
table. If the source table holds the primary key, it cannot have a primary or foreign key relationship with the target table. If the target table holds the foreign key, it cannot have a primary or foreign key relationship with the source table.
In summary, simple tables can easily accommodate partition switching. The more complexity a source or target table exhibits, the more likely that careful planning
and extra work will be required to even make partition switching possible, let alone efficient.
Here’s an example where we create a partitioned table using a previously created partition scheme, called Date_Range_PartScheme1.
We then create a new, nonpartitioned table identical to the partitioned table residing on the same filegroup. We finish up switching the data from the partitioned table into the nonpartitioned table:
CREATE TABLE TransactionHistory_Partn1 (Xn_Hst_ID int, Xn_Type char(10)) ON Date_Range_PartScheme1 (Xn_Hst_ID) ; GO CREATE TABLE TransactionHistory_No_Partn (Xn_Hst_ID int, Xn_Type
char(10)) ON main_filegroup ; GO ALTER TABLE TransactionHistory_Partn1 SWITCH partition1 TO TransactionHistory_No_Partn; GO
The next section shows how to use a more sophisticated, but very popular, approach to partition switching called a sliding
window partition.
Example and Best Practices for Managing Sliding Window Partitions
Assume that our AdventureWorks business is booming. The sales staff, and by extension the AdventureWorks2012 database, is very busy. We noticed over time that
the TransactionHistory table is very active as sales transactions are first entered and are still very active over their first month in the database. But the older the transactions are, the less activity they see. Consequently, we’d like to automatically group
transactions into four partitions per year, basically containing one quarter of the year’s data each, in a rolling partitioning. Any transaction older than one year will be purged or archived.
The answer to a scenario like the preceding one is called a sliding window partition because
we are constantly loading new data in and sliding old data over, eventually to be purged or archived. Before you begin, you must choose either a LEFT partition function window or a RIGHT partition function window:
1. How
data is handled varies according to the choice of LEFT or RIGHT partition function window:
• With a LEFT strategy, partition1 holds the oldest data (Q4 data), partition2 holds data that is 6- to 9-months old (Q3), partition3
holds data that is 3- to 6-months old (Q2), and partition4 holds recent data less than 3-months old.
• With a RIGHT strategy, partition4 holds the holds data (Q4), partition3 holds Q3 data, partition2 holds Q2 data, and partition1
holds recent data.
• Following the best practice, make sure there are empty partitions on both the leading edge (partition0) and trailing edge (partition5)
of the partition.
• RIGHT range functions usually make more sense to most people because it is natural for most people to to start ranges at their lowest
value and work upward from there.
2. Assuming
that a RIGHT partition function windows is used, we first use the SPLIT subclause of the ALTER PARTITION FUNCTIONstatement
to split empty partition5 into two empty partitions, 5 and 6.
3. We
use the SWITCH subclause
of ALTER TABLE to
switch out partition4 to a staging table for archiving or simply to drop and purge the data. Partition4 is now empty.
4. We
can then use MERGE to
combine the empty partitions 4 and 5, so that we’re back to the same number of partitions as when we started. This way, partition3 becomes the new partition4, partition2 becomes the new partition3, and partition1 becomes the new partition2.
5. We
can use SWITCH to
push the new quarter’s data into the spot of partition1.
Tip
Use the $PARTITION system
function to determine where a partition function places values within a range of partitions.
Some best practices to consider for using a slide window partition include the following:
• Load newest data into a heap, and then add indexes after the load is finished. Delete oldest data or, when working with very large
data sets, drop the partition with the oldest data.
• Keep an empty staging partition at the leftmost and rightmost ends of the partition range to ensure that the partitions split when
loading in new data, and merge, after unloading old data, do not cause data movement.
• Do not split or merge a partition already populated with data because this can cause severe locking and explosive log growth.
• Create the load staging table in the same filegroup as the partition you are loading.
• Create the unload staging table in the same filegroup as the partition you are deleting.
• Don’t load a partition until its range boundary is met. For example, don’t create and load a partition meant to hold data that is
one to two months older before the current data has aged one month. Instead, continue to allow the latest partition to accumulate data until the data is ready for a new, full partition.
• Unload one partition at a time.
• The ALTER TABLE...SWITCH statement
issues a schema lock on the entire table. Keep this in mind if regular transactional activity is still going on while a table is being partitioned.
Thanks Shiven:) If Answer is Helpful, Please Vote

Error when applying data filters on Logical Dimensional Table

I have a data filter setup on a dimension table using session variables. The session variables are getting populated in the correct way. To make sure, I created an analysis with session variables, and I see the values that I need to apply the data filters.
When I select a column from the dimensional table in the presentation services, I am getting below error.
Error getting drill information: SELECT "GL Segment3 - Office"."Region Code" saw_0 FROM "Financials - AP Overview"
Error Details:
Error Codes: YQCO4T56:OPR4ONWY:U9IM8TAC:OI2DL65P
Odbc driver returned an error (SQLExecDirectW).
State: HY000. Code: 10058. [NQODBC] [SQL_STATE: HY000] [nQSError: 10058] A general error has occurred. [nQSError: 43113] Message returned from OBIS. [23014] The Variable with Object ID '3031:338998' is still referenced and could not be loaded.Please have your System Administrator look at the log for more details on this error. (HY000)
SQL Issued: {call NQSGetLevelDrillability('SELECT "GL Segment3 - Office"."Region Code" saw_0 FROM "Financials - AP Overview"')}
Thanks,
-Amith.
Edited by: Amith on May 3, 2011 12:19 PM

You can go into the BI Administration tool, then go to tools. After that go to Query Repository.
In the "name" field leave the "*". Set the "type" to variable and do not establish a filter.
Once you hit query you should see all of the repository variables listed and you can see the code that is throwing you the error. Although, in my case it is throwing me a code that does not exist in this list. I'm a bit stuck as well.
Anyone?

In Answers am seeing "Folder is Empty" for Logical Fact and Dimension Table

Hi All,
Am working on OBIEE Answers, on of sudden when i clicked on Logical Fact table it showed me as "folder is empty". I restarted all the services and then tried still showing same for Logical Fact and Dimension tables but am able to see all my reports in Shared Folders. I restarted the machine too but no change. Please help me out to resolve this issue.
Thanks in Advance.
Regards,
Rajkumar.

First of all, follow the forum etiquette :
http://forums.oracle.com/forums/ann.jspa?annID=939
React or mark as anwser the post that the user gave.
And for your question, you must check the log for a possible corrupt catalog :
OracleBIData_Home\web\log\sawlog0.log

Help on Setting logical Levels in Fact tables and on Dimension tables

Hi all
Can any body provide any blogs or any king of material on what exactly is levelling .
Like after creating the Dimensional hierarchies we need to set the logical levels for the LTS of fact tabels ri8 .So what is the difference between setting logical levels to fact tabels and also Setting levelling on Dimension tables .
Any kind of help is appreciated
Thanks
Xavier.
Edited by: Xavier on Aug 4, 2011 10:50 AM

I have read these blogs ,but what my question is
Setting the logical levels in LTS of Fact tables i understood .
But we can also set the logical levels for dimensions also ri8 .I didn't understand why do we set the logical levels for dimensions .Is there any reason why we go with the levelling at dimensions
Thanks
Xavier
Edited by: Xavier on Aug 4, 2011 2:03 PM
Edited by: Xavier on Aug 4, 2011 2:32 PM

Best practice when FACT and DIMENSION table are the same

Hi,
In my physical model I have some tables that are both fact and dimension table, i.e. in the BMM they are of course separated into Fact and Dim source (2 different units) and it works fine. But I can see that there will be trouble when having more fact tables and I e.g. have a Period dimension pointing to all the different fact tables (different sources).
Seems like the best solution to this is to have an alias of the fact/transaction table and have 2 "copies" of the transaction table (one for fact and one for dimension table) in the physical layer. Only bad thing is that there will then allways be 2 lookups in the same table when fetching data from the dimension and the fact table.
This is not built on a datawarehouse - so the architecture is thereby more complex. Hope this was understandable (trying to make a short story of it).
Any best practice on this? Or other suggestions.

Id recommend creation of a view in the database. if its an oracle DB, materialised views would be a huge performance benefit. you just need to make sure that the MVs are updated when the source is updated.
-Domnic

How to show current date in a column of dimension table in ssas

Hi,
I have 2 dimension tables (ALLWORK and YOURWORK) and 1 measure table (STATS). In ALLWORK dim table, I have 4 columns, one of them is END_DATE. Based on END_DATE and current date I want to create a named calculation field. To achieve this, I
want to show the current date in 5th column (of ALLWORK dim table) as calculated member (as named calculation wont show me correct date).
Problem is, I am not able to create the column in the dimension table. While creating the calculated member, I am not able to select the ALLWORK dimension table, it always selects MEASURE by default. Please help.
thanks
Tarique
thanks and regards Tarique Aslam

Hi Tarique,
According to your description, you want to add a column to your dimension to show the current date, right?
In data source view, we can add named calculation to your table. A named calculation is a SQL expression represented as a calculated column. This expression appears and behaves as a column in the table. A named calculation lets you extend the relational
schema of existing tables or views in a data source view without modifying the tables or views in the underlying data source.
Reference
http://msdn.microsoft.com/en-in/library/ms174859.aspx
http://devmau5.wordpress.com/2010/03/25/the-getdate-of-mdx/
If I have anything misunderstand, please point it out.
Regards,
Charlie Liao
TechNet Community Support

Multiple columns from the same dimension table as row labels performing slowly

(Working with SSAS tabular)
I'm trying to figure out what the approach should be for the following scenario:
Lets say we have a Customer table. The table has columns such as account number, department number, name, salesperson, account manager, number of customers, delivery route, etc
A user of the model could want to see any permutation of that information as the row labels. How should that be handled?
What we've been doing so far is that the user adds each column they want into the "ROWS" section in Excel. This works fine with smaller tables (for example, "Department" table with a "Department Code" and "Department Name",
but on large tables this quickly chokes. I understand why this is happening, I just haven't found a better way to accomplish the same thing.
I can add a calculated column to the model through VS, but obviously this is unsupportable and unscalable when each person needs their own permutations of the data. Can something similar be done in Excel?
This question seems to be what I need:
http://social.msdn.microsoft.com/Forums/en-US/97d1157a-1402-4227-b96a-79524401ddcd/mdx-query-performance-when-selecting-multiple-attributes-from-same-dimension?forum=sqlanalysisservices
However I can't find any information on how to add those properties (is it a multidimensional-only thing?)

Thanks for the help. Sorry but i'm a self-taught developer, and i may be missing some basics :)
Anyway i've done what you suggested but i get this error:
[nQSError: 15011]The dimension table source Dimension Services.DM_D_SERVIZI_SRV has an aggregate content specification that specifies the level Product. But the source mapping contains column COD_PRODUCT with a functional dependency association on a more detailed level .
where:
- DM_D_SERVIZI_SRV is the physical alias for the Service Dimension (and the name of the LTS too)
- COD_PRODUCT is the leaf of the hierarchy, the physical primary key, but it hasnt to be included in the hierarchy
Do i have to add another level with the primary key and hide it to the users?
I tried to solve this going to the logical tables source properties, on the tab contents, setting "logical level" to null for the hierarchy, but i don't know if this is correct.
Thanks

How to find out the infoProvider for a given dimension table?

Experts:
In RSA1, I want to find out the infoProvider for a given dimension table.
But I am not sure how to display the tables linked to a given infoProvider.
Could you provide a way to display all tables linked to a given infoProvider?
Thanks a lot!

See, The dimension table starts with Dcubename1 and incremental Dcubename2 .... so on
Ex.ZSD_C01 is your cube name
Dim tables starts for this is /BIC/DZSD_C011 /BIC/DZSD_C012 ...
Goto - LISTSCHEMA - derive cube name from given dim table and enter cube name - execute - will show you all the tables

Should my dimension table be this big

Im in the process of building my first product dimension for a star schema and not sure if im doing this correctly. A brief explanation of our setup
We have products (dresses) made by designers for specific collections each of which has a range of colors and each color can come in many sizes. For our UK market this equates to some 1.9 million
product variants. Flattening the structure out to Product+designer+collection gives about 33,000 records but when you add all the colors and then all the colors sizes it pumps that figure up to 1.9million. My “rolled own” incremental ETL load runs
ok just now, but we are expanding into the US market and our projections indicate that our products variants could multiple 10 fold. Im a bit worried about performance of the ETL just now and in the future.
Is 1.9m records not an awful lot of records to incrementally load (well analyse) for a dimension table nightly as it is never mind what that figure may grow to when we go to US?
I thought of somehow reducing this by using a snowflake but would this not just reduce the number of columns in the dimensions and not the row count?
I then thought of separating the colors and size into their own dimension, but this doesn’t seem right as they are attributes of products and also I would lose the relationship between products, size & color I.e. I would have to go through the
fact table (which ive read is not a good choice.) for any analysis.
Am I correct in thinking these are big numbers for a dimension table? Is it even possible to reduce the number somhow?
Still learning so welcome any help.
Thanks

Hi Plip71,
In my opinion, It is always good to reduce the Dimension Volume as much as possible for better performance.
Is there any Hierarchy in you product Dimension?.. Going for a snowflake for this problem is a bad idea..
Solution 1:
From the details given by, It is good to Split the Colour and Size as seperate dimension. This will reduce the vloume of dimension and increase the column count in the fact(seperate WID has to be maintained in the fact table). but, this will improve the
performance of the cube. before doint this please check the layout requirement from the business.
Solution 2:
Check the distinct count of Item varient used in fact table. If it is very less, they try creating a linear product dimension. i.e, create an view for the product dimension doing a inner join with the fact table. so that only the used Dimension member will
be loaded in the Cube Product Dimension. hence volume is reduced with improvement in performance and stability of the cube.
Thanks in advance, Sorry for the delayed reply ;)
Anand
Please vote as helpful or mark as answer, if it helps Regards, Anand

Issue using one 2 Fact tables with one dimension Table.

Hi,
I have 1 Dimension table X and 2 Fact tables A and B
X is joined to Both A and B for Loan Amount ( with A) and for colleatral amount (with B) when I am selecting the X.Product_Name, A.Loan_Amt, B.Collateral Amount, it is giving an error message
State: HY000. Code: 10058. [NQODBC] [SQL_STATE: HY000] [nQSError: 10058] A general error has occurred. [nQSError: 15018] Incorrectly defined logical table source (for fact table EIP Collateral FACT) does not contain mapping for [EIP Reporting FACT.PD ID]. (HY000)
Any clues???
Is there a Inner or Outer join which needs to be created or set in the RPD to get the desired results???

Ok..
I have one table which is Porfolio Details which has Portfolio name, Product Category , Product Name, Product ID, Product sources code.- This is my Dimension table.
I have another 2 set of fact tables : EIP Reporting FACT and EIP Collateral FACT..
These two tables are joined to Portfolio Details table.
EIP Reprting FACT gives portfolio wise Loan Amount
and EIP Collateral FACT gives Portfolio wise Collateral Amount details for same set of customer..
Now, I am selecting Portfolio Name, Product Category, Product Name,SUM( EIP Reporting FACT.LOAN_AMOUNT), SUM(EIP Collaetral FACT.Collateral_Amt) in a report
Now, on selecting these columns I am getting that error message which is related to mapping.
If I take any column from Portfolio details table and any column from EIP Reporting FACT- It works.
If I take any column from Portfolio details table and any column from EIP Colletral FACT- It works.
But if I take any column from portfolio table and columns from both FACT tables it gives mapping error...
Hope I am able to explain the issue in a better way now..
Edited by: help-required on Mar 11, 2010 6:53 PM
Edited by: help-required on Mar 11, 2010 6:53 PM

Consistency Warning - [39008] Dimension Table not joined to Fact Source

I have a schema in which I have the following tables:
A) Patient Transaction Fact Table (i.e. supplies used, procedures performed, etc.)
B) Demographic Dimension table (houses info like patient location code)
C) Location Dimension table (tells me what Hospital each unique Location maps to)
So table A is the fact, and table B is a dimension table joined to table A based on Patient ID, so I can get general info on the patient. This would allow me to apply logic to just see patient transactions where the patient was FEMALE, or was in the Emergency Room, by applying conditions to these fields in table B.
Table C is a simple lookup table joined to table B by Location Code, so I can identify which hospital's emergency room the patient was located in for instance.
So the schema is: A<---B<---C, where B and C are both dimension tables.
The query works as desired, but my consistency check gives me the following WARNING:
*[39008] Logical dimension table LOCATION MASTER D has a source LOCATION MASTER D that does not join to any fact source.*
How do I resolve this WARNING, or at least suppress it?

Hi,
What you need to do is to add the (physical) location dimension table to the logical table source of the demographic dimension, for example by dragging it from physical layer on top of logical table source of demographic logical dimension table in bmm layer
Regards,
Stijn

Multiple Fact Tables and Dimension Tables

I have been having some problems trying to model the data from Oracle E-Business Suite maintenance. I will try to give the best description of how the data is held in the tables. The structure is such that a work order can have multiple operations and an operation can have multiple resources as well. I believe the problem comes in the fact that an operation doesn't necessarily need to have a resource. I could not attach an image so I have written out an example below. I am not saying this is right or that it works, but just to give you an idea of what I am thinking. The full dimension would be Organization -> WorkOrder -> Operation -> Resource. Now, the fact tables all hold factual data for the three different levels, with the facts being at each corresponding level. This causes an obvious problem in combining the tables into one large fact table through the ETL process.
Can anyone tell me if they think this can be done? Am I way off? I am sure that there is a solution as there always is but I have been killing myself trying to figure this one out. I currently have the entire solution in different Business Models. I would like however to be able to compare facts from multiple areas such as the Work Order level and the Resource level.
Any help is greatly appreciated. I realize that the solution may also require additional work on the ETL side so I am open to any and all suggestions.
Thank you in advance for anyones time. :)
Dimension Tables
WorkOrder_D
Operation_D
Resource_D
Organization_D
Fact Tables
WorkOrder_F
Operation_F
Resource_F
Joins
WorkOrder_D -> Operation_D
Operation_D -> Resource_D
WorkOrder_D -> WorkOrder_F
Operation_D -> Operation_F
Resource_D -> Resource_F
Organization_D -> WorkOrder_D
Organization_D -> Operation_D
Organization_D -> Resource_D

Hi,
Currently the dimension table is taken as a simple logical table in rpd as it does not have have any levels or hierarchy.
Its a flat dimension. Can you guide me how can I implement a flat dimension in OBIEE? Because this dimension is taken as simple logical table
I am not able to set appropriate level for fac tables. This dimension does not appear in the list of dimensions.

Filtering on a dimension table

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