SSAS Joining Facts at different granularity to a single dimension:

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Problem:

You have a Fact Sales and Fact Target in your data mart. Fact Sales stores values are product sub category level and fact target stores values at product category level because business sets “sales targets” at a higher (rolled up) level. How do you connect it to a single dimension at different granularity?

Solution:

Here’s the table structure, I just made this up for the demo purpose:

Fact Sales Table

1. Fact Sales

Fact Target

2. Fact Target

Product Sub Category Table

3. Dim product sub category

so, you went ahead and tried testing by creating relationship’s to single dimension at different granularity in the cube:

SSAS Dimension Usage RelationshipsNote how the relationship was specified between Fact Target and Product Sub Category Dimension – it’s joined at a different granularity compared to fact sales. it would be help you from a performance standpoint if the fields that you are using to join the fact and dimension is an int.

SSAS Relationship Dimension Usage Regular

So, you browse the cube and here’s what you get:

Excel SSAS Analysis Services

Note the problem: the target values are being repeated for sub categories but that shouldn’t be happening, right? that’s misleading to business users…ok, to recap what we need to do here: hide target values for subcategories since targets are not set at that granularity. but we do need to show them if the business users pulls in product category.

So here’s a measure group property that comes to the rescue!

Go to Fact Target Measure group’s property > Set IgnoreUnRelatedDimension to False

SSAS Ignore Unrelated Dimension Property

deploy and browse your cube again, here’s what you will see now:

Excel SSAS Analysis Services Pivot Table

That’s it! you have successfully joined facts at different granularity to a single dimension.

SQL Server Analysis services – How to set the order by attribute sort key?

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Problem:

How to sort the dimension attribute by something other than the key and name column? How do you set the “OrderBy” property?

Example: You have created an Inventory age buckets 1-50,51-100,101-150 and so if a business user uses this dimension attribute then the sorting won’t be logical. It would be 1-50, 101-150,51-100 – so how to show the buckets in the logical order?

Solution:

1. make sure that the table/view that you are bringing in has the sort key.

Example:

1 SSAS Attribute order by sort key2. Now, switch to SSAS and open your dimension. I am assuming that you’ve already configured your data source views and you are already bringing in these columns in the dimension:

Dim Inventory SSAS SSIS VIEW Data source VIEW

3. Let’s start with hiding Aging Bucket Sort key so that it’s not visible to user. Change the AttributeHierarchyVisible to False

4. Now, switch to Attribute Relationships – Right Click on Aging Bucket and click on New Attribute Relationship. And set the attribute relanship between Aging bucket and Aging Bucket Sort Key

Attribute Relationships SSAS

And you should see something like this in your attribute relationship section:

SSAS Attribute Relationship Sort Key

5. Now, one more thing to configure. Go back to dimension structure section. Open the properties section for the Aging Bucket Attribute and change the OrderBy property to AttributeKey. Also, change the orderByAttribute property to Aging Bucket Sort Key (in your case, choose the sort key that you have)

SSAS Order Sort by attribute property

That’s it, after you process the model then you should see the attribute being sorted based on the sort key that you had.

Conclusion:

In this post, you saw how to configure sort/order property of a dimension attribute.

SQL Server Analysis Services (SSAS) multidimensional cube: How to create a role playing dimension?

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Summary:

I was recently asked by a SSAS developer about how to set up a role-playing dimension so I did a brief demo to show how to set it up. In this post, I am document the steps to help you get started:

What is role-playing dimension?

What if you want to see sales data by Order Date as well as Shipped Date? You can one date dimension that is used more than once for seeing sales data by order date and shipped date. In this case, date dimension becomes a Role Playing Dimension.

Steps:

1. Open SQL Server Data Tools and SSAS project that you are working on.

2. Go to Data Source Views from the solution explorer.

3. Make sure that the relationships are specified between dimension (e.g. date dimension) and Fact Table (e.g. Fact Sales). Example: If you’ve OrderDateSK and ShippedDateSK in your fact table, then establish a relationship between the both columns with the Primary Key of the Date dimension.

SSAS Data Source View Role playing dimension

Note: If you do not have the relationships specified in the data source views, there’s an alternative to go to dimension usage for a cube and setup role playing dimensions. since this is targeted to get you started, I am not covering the steps for that.

4. Now go to the Dimensions section in the solution explorer and add a Dimension that uses the existing data source view from step #3.

5. switch to Cubes.

Now, if you don’t have a cube created yet then you can use the cube wizard if you want and as long as you have the relationships specified at DSV’s, it should create a role-playing dimension.

Alternatively, you can also create a new dimension. In the Design pane, lower left section, you’ll see dimensions.

Add Dimensions Cube SSAS

select your dimension that you created in step #4 that’s a role-playing dimension from the list and click on OK. And it creates a role-playing dimension for you! So all you had to do was to make sure the relationships are created between the fact and (role-playing) dimension table and SSAS does the rest of the work for you

SSAS Role Playing Dimension

 

Note: for the demo I didin’t rename the dimension attributes but you do all that good stuff too when you are building the cube for users!

Conclusion:

In this post you got started on how to add a role-playing dimension in a SSAS cube.

SSAS Multidimensional cube: How to solve duplicate attribute key error when attribute is non key?

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Problem:

In SSAS multidimensional cube, while processing a cube, you get an error/warning for a non-key “price” column that says:

Errors in the OLAP storage engine: A duplicate attribute key has been found when processing: Table: ‘Table Name’, Column: ‘Price’, Value: ’29’. The attribute is ‘Price’.

You see, if it would complain about a key column having duplicate attribute that would have been fine but it’s complaining about duplicate attribute key when an attribute is non key. How do you solve this?

Solution:

mostly this is because that the view/table that you are using in your data source views have blanks/nulls.

so in your source, use ISNULL/COALESCE TSQL function before bringing data in the cube OR if it makes sense for you then you can filter out blank data too.

I hope that helps.

SSAS Tabular: How to mark a table as Date Table?

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Problem:

For time intelligence in SSAS Tabular models, it’s important to mark a date table. So, how do you do that?

Solution:

Here are the steps:

1. After you have the data imported in a table, in the model designer, select the date table

2. Also, make sure that necessary relationships are created between date table and fact tables.

3. Now, on the menu bar, select Table > Date > Mark as Date Table

SSAS Tabular mark as date table4. A dialog box should ask you for a unique identifier of the date table, so it could be a date column which has the unique columns for the date table that you imported.

Also, make sure that the unique identifier does not have blank values because the model designer will not allow you to select it as your unique identifier and so you may have to go back to your table properties and put a logic to filter out blank values or make sure that the a row with blank value has a value assigned to it.

After you do that, you’re all set to go! I hope this helps.

SQL server analysis services MDX: Current Fiscal Period vs Previous year same Fiscal Period Query

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Problem:

Comparing data current fiscal period vs previous year same fiscal period query is a very common problem. Here’s a sample query.

Solution:

Please use the query as a staring point for current fiscal period vs previous year same fiscal period. I used the Contoso Cube to come with the query. The key part is to use the PARALLELPERIOD function.

[code language=”SQL”]

with member [Sales Amount Previous Year Fiscal Month] as
SUM(ParallelPeriod([Date].[Fiscal Month].[Fiscal Month],12,[Date].[Fiscal Month].CurrentMember ),[Measures].[Sales Amount] )

select
{[Measures].[Sales Amount],[Sales Amount Previous Year Fiscal Month]} on 0,
NON EMPTY {[Date].[Fiscal Month].[Fiscal Month]} on 1
from
[Sales]

where
[Date].[Fiscal Year].&[2008]

[/code]

MDX current year vs previous year same fiscal periodConclusion:

In this post, I shared a MDX query that you can use for current fiscal period vs previous year same fiscal period.

SQL server Analysis Services: How to import cube meta data to SQL server Data Tools?

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Problem:

Someone on your team deployed a cube and gave you access to it. Now, as an IT developer on the team you want to know the calculation that was used for some of the measures. How do get it? You can email the contact person, right? Sure, but let me show you how you can decrease email back and forth using the following steps.

Note: it’s applicable to both multidimensional model as well as tabular model.

Solution:

1. Open SSDT

2. File > Project > New

3. Installed Templates > Business Intelligence > Analysis services > Import from Server

SQL Server Analysis Services Business Intelligence Import

4. You’ll get a dialog box, enter server name and the cube/model metadata that you want to import

Import Microsoft Business Intelligence analysis cube

5. In the solution explorer, you should be able to see the cube meta data! Now, you can go look at the measure calculation that you wanted to see, or may be the KPI rule? or something else in the cube that you needed to know.

Conclusion:

In this post, I described how you can import SQL server analysis services cube/model from the server.