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### Aggregations based on Dimensions dragged for Calculated measure from different fact table Using MDX

Hi,

I am a newbie to Mdx, i am working on education domain. I have a requirement to calculate student counts based on different fact views.

Especially for state,district and school levels we created three different fact views based on applying some conditions on original fact table.

Now i am using only one calculated measure named "Student Count" in my cube. My requirement is, when i drag my district dimension student count count based on district dimension should appear in my measure, if drag both districts and schools together then school facts student count should appear in my count, if i didn't drag any of the two dimensions then state level count defaultly aggregated.

For this, i thought write an mdx basing on dimension i am dragging, so i started with scope function for getting a different fact view based on different fact view,

Scope([Districts].[Districts],[Mesures].[Student Count])

this= ([Districts].[Districts],[Mesures].[District Student Count])

end scope;

like wise for school dimension and so on, but i am getting same value for both of the cases.

could any one help me out in getting solution for this. Is there anyother way other than creating new cubes for each level.

Thanks in advance. Any suggestions are appreciated.

Lakshman A N, S

### overriding "grand totals" for calculated members

hi all, is there a workaround for overriding "grand totals" for calculated members?  (I cannot use the workaround whereby I create the calculation in the DSV or view directly due to it being a pretty complex Descendant parent/child calculation).   thanks much for any thoughts, Cos

### Relationship between a dimension - two fact tables

I have 3 fact tables and about 10 dimensions. I want to relate both "Fact_Pop1" and "Fact_pop2" to Dim_AgeGroup. But Fact_pop1 has single age group and Fact_pop2 has no single age group (5 years age group). I spent about a day on this but I could't solve it.   Fact_Pop1 Age        Race_key            Gender_key      Geography_key              Pop_size 10           White                    M                                            CA                          10000    10           White                    F

### Fact table in DSV vs partitions pointed to a different table

I am seeing an issue in my cube for a partition that is based on a separate table than the Fact table in the DSV. I have 8 partitions all from different physical tables. In the DSV I used 1 of those 8 partition tables as the "source" of the DSV so I could model the relationships between the fact and the dimensions. On 1 of the 8 it loads over 1 million rows from the partition into the cube, but when I use the browser to show the count in that particular partition it shows the exact same number of records that are in the table that was used in the DSV. The strange thing is all the other partitions work fine except this 1. I have deleted the partition and added it back multiple times and cant get it to work right. Has someone seen this problem before?   I have run into this a couple times, one way of fixing it was to recreate the entire project in a new project, copy all objects from the old projects and rebuild. I cant seem to figure out another way of fixing this.Craig

### Building Fact and Dim table

How to build Fact and Dim tables for below requirement. Fact records (approx 800k) has to be analyzed every day w.r.t AgeGroup's Every record in fact will have a DOBSID and age/agegroup should be calculated every day based on getdate()

### Count of fact rows not being displayed correctly

I have the most generic measure - count of rows from the fact table. When I query the underlying fact table, example...select count(Primary_key) , I get accurate results. Also, I see my partition has exact same count for the rows. But, when I process the cube and view the same measure in the browser it shows less than the actual count . I never had this problem before. What could I be missing? I would appreciate your suggestions.   Rok

### Getting counts by 2nd Date Dimension Attribute with Snapshot Style Fact Table

I have an MDX question finding hard to solve.  I have a Snapshot Fact Table with a snapshot of the records in the source system for each batch date.  All records in the fact table are assigned the batch date with the batch date key.  There are many records for each day and each batch date is an entire copy of the source records.  So, the grain of the fact table is one record for each batch date that exists in the source system.  These facts rows have another date in them for when the record was entered.  This date is different from the batch date in that the batch date is based on the day the batch was processed and the entered date is based on when the record was entered.  If a record was entered many days before, its batch date will be today but its entered date will be several days ago.  Therefore each day a copy of all the records entered the previous batch date and all the records added on today's batch date are present. Fact Table : FactSnaphshotKey (surrogate for easier administration) BatchDateKey (link to batch date dimension – date dimension, first in dimension list so it is used for semi aggregate measures) EnteredDateKey (link to entered date dimension – date dimension) Facts Count – measure for fact table - default measure from Analysis Services cube 2 Dim

I am aware that when adding a row group, a prompt asks you if you want to add the header and footer.  On my report, all the groupings are already created and do not want to have to recreate them again;  how can I add just the row group header? I can't seem to find the option   Thanks!Javier Guillen

### Update an accumlating shapshot fact table

This is my first time implmenting an accumulating snapshot fact table and I require some guidance. Accumulating snapshot fact tables show the status at any given moment. It is useful to track items with certain life time, for example: status of order lines.eg everytime there is new piece of information about a particular purchase, we update the fact table record. We only insert a new record in the fact table when there is a new purchase requisition. What I really need to know is how best to handle the updates.  This really feels very similar to managing SCD-1's in dimension processing! Anyone able to advise? thanks in advance Here is a perfect example we can use  http://blog.oaktonsoftware.com/2007/03/accumulating-snapshot-use-accumulating.html Figure 1, below, shows an accumulating snapshot for the mortgage application process. The grain of this fact table is an application. Each application will be represented by a single row in the fact table. The major milestones are represented by multiple foreign key references to the Day dimension—the date of submission, the date approved by mortgage officer, the date all supporting documentation was complete, the date approved by an underwriter, and the date of closing.

### Long list of calculated members

·         I have a long list of calculated members. How can I make this long list user friendly like categorizing them by functionality? Can I create measure group for calculated measures?   Alex

### daily complete cube rebuild four dimensions and fact table including remapping of all surrogate keys

Hi SSIS Engineers: Forgive me if this is a multi-forum question. Our primary activity in the next week is to automate the processing in SSIS, where I led the team to create complete processing flows for Full and Add in the order of Dimension, Measure Group, Partition, Cube, Database. These work. The problem occurs in a complete refresh of the ERP database that caused me manual effort inside SSAS, which I plan to find a way to automate in SSIS. I performed a complete refresh of our cube from the ERP source from a time perspective. We are automating this process in SSIS. In SSAS, I had to manually delete the four dimensions from the UDM view via the Solution Explorer. Since the complete refresh increased the surrogate keys in the dimensions and since the names were the same, I couldn't just drop the partition and reprocess the dimensions, since, in effect, new fact rows would have to be mapped to the new keys. SSAS held on to the old keys even with Full Processing of the Dimensions first, then the Cube. Until I dropped--deleted-- the dimensional tables from the Solution Explorer and the UDM then later readded the dimensions with the new surrogate keys (both add, update and delete dimensional attribute changes in full refresh) via the Add Dimension wizard, the cube kept the old surrogate keys and failed in measure group, fact, database and partition processing.

### Non parent-child dimension with fact data at different levels... How!

Hi all, Quite new to SSAS, wondering if anyone could help with the following... I've got a dimension with attributes that indicate geographical location based upon UK postal boundaries - so ~1.8m Postcodes > ~10000 Postcode Sectors (PCDS) > ~3000 Postcode Districts (PCD) > ~100 Postcode Areas (PCA). The problem I have is that the address information is not of the highest quality. I have matched 50% of my facts to postcodes, of the remaining 50% i've mapped them to PCDS, PCD or PCA, where possible, leaving the lower-levels as NULL in those cases. My attribute hierarchy works fine where I have complete records all the way down the hierarchy, but I only have a single UNKNOWN member at the top (GOR) level. I want an UNKNOWN member at each level. It makes sense to me how to do this using a Parent-Child dimension, but i'm keen to avoid that as the performance is terrible. I'm hoping there's a method of configuring this. Any help massively appreciated.

### MDX query performance is slow for complex logic implementation in Calculated Members.

We have implemented a calculated members which involves multiple calculated members  called in a nested e.q. Cal1 calls Cal2 and Cal2 calls  Cal3  and Cal3 calls Cal4 .  And when browing Cal1 through Excel it takes around 30 mins for getting result from a Partition having row count around 5 million. Follwing are the information on the scenario I am having: We are having partitioning in the cube. one partition contains around 4-6 million records Processers on Query Server: 4 quad core RAM on the Query Server: 64 GB Calculated members having simple calculation logics are giving results in no time. There is a Calculated members which calls 6 intermediate calculated in nested way and with small Data Set like 5-6 k rows it is running fine.   Any help will be much appreciated.   Regards, Sandeep

### Considering Holap fact group when requesting large amount of leaf cells

We have a MOLAP fact group which is often queried at the leaf level, with sets of 200 or more records. Holap is considered to have a medium query performance, but, i'm considering Holap because of the large amount of records which can be retrieved ad-hoc from the DWH who do not have aggregations. I would think Holap is more effective in this scenario as I'd think a sql query is faster than a Molap query when you want large sets of leaf data.  What are your experiences/strategies when large sets of leaf data need to be queried ? Do you share this idea that Holap is faster on large sets of leaf data than Molap?Business Intelligence professional

### Avoiding a SELECT distinct query generated by SSAS when using dimension derived from fact table

Hi, I am using a dimension derived out ot a fact table and the factt able primary key is dimension key. Issue is, there are large number of rows and so many attributes. SSAS issues distinct query and it takes large amount of time. Without the distinct statement, query takes only 3 min for 4 million rows. With the distinct, it takes 20 min. Becuase the fact primary key is the dimension key there is no need of a distinct statement. I know there is a option in the dimension to say "By Table" to avoid this. But unfortuantely, i breach the 4 GB limit for strings. Any suggestions for optimization? Thanks,  Sambath

### Need multiple distinct counts, have 1 fact and 1 dimension

I am using SSAS 2005. I have 1 fact table and 1 dimension. I would like to create multiple distinct counts in 1 Measure group, at least I would like them to appear as in 1 measure group to end-user. I have tried role-playing dimensions, and a roll your own approach that work in limitation but didn't scale. Any help and advice would be great.

### Join two fact tables

Hi,

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I have the following two fact tables, upon which a cube was built. As you can see, these two tables have most of theÃÂ common (shared) dimensions except for ProductTypeID (product dimension) on fct_productsales table. The relationship between these two fact tables is 1(fct_loansales) to Many (fct_productsales).

When I browse these measures from the cube, they look fine (and break down perfectly) through all the shared dimensions.

However, when I try to filter or browse through product dimension (along with other dimensions), the measure values from fct_productsales will filter down correctly, but the values from fct_loansales does not change.ÃÂ  I tryied to create degenerate dimension from fct_loansales, but no luck. Any help is appreciated.

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Fct_LoanSales

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