In this part of the tutorial we will decorate the UDM with some attributes and will generate the relational database schema.
We will start with the attributes of the MSA dimension. Looking back at the data source, we see that the MSA dimension (columns A and B) contains three levels of hierarchy - Region (Northeast, Midwest, etc.), Sub-region (New England, Middle Atlantic, etc.), State and the lowest level - MSA. So we have total of four attributes including the key attribute.
We manually add the attributes to the MSA dimension:

Then we add the Month and Year attributes to the Time Period dimension:

The Employment Category dimension is flat - there is no hierarchical structure to it, so we’ll leave this dimension alone.
It is time to generate the schema now.
Follow these steps to get this done:
- Launch SQL Server Management Studio, connect to SQL Server Database Services and create a new relational database - we’ll call this database “Employment BI”:
- Go back to Business Intelligence Development Studio and create a new data source in the SSAS project - right-click on the “Data Sources” icon in the solution explorer and select “New Data Source”. Provide the necessary information to create the data source connection to the “Employment BI” relational database.
Here’s a snapshot of my settings:

For impersonation mode I usually select to have SSAS impersonate my windows account by selecting “Use the service account” in the Data Source Wizard, but feel free to select whatever makes sense in the context of your security settings:

Go through the Data Source wizard and when prompted, name the data source “Employment BI”. - Launch the Schema Generation Wizard by selecting “Database\Generate Relational Schema…”
- On the first screen select “Create a new data source view”, name the new data source “SSAS” and select the “Employment BI” data source:

- On the next screen uncheck the settings to preserve referential integrity and to preserve data on regeneration:
- Leave the naming conventions page as is and click “Finish”
The Schema Generator produces the entire relational schema and an SSAS data source view based on the metadata we provided earlier. Here’s a snapshot of the data source view:
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The generator has produced two fact tables: Employment_Facts and Unemployment_Facts and three dimension tables: Employment_Category, Time_Period and MSA.
Note that the schema follows Kimball’s guidelines for keeping the dimensional tables denormalized. In other words the Schema Generator favors denormalized star schema over normalized snowflake schema. In a star schema all the attributes of a dimension are collapsed together in a single table to avoid complex and slow multi-table joins when data is queried.
In the next post we will finish this mini-project by creating an SSIS project to populate the dimensional model with the data captured in the Excel spreadsheet.
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