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Filtering a Nested Table in a Mining Model (Intermediate Data Mining Tutorial)

Applies To: SQL Server 2016 Preview

After you have created and explored the model, you decide that you want to focus on a subset of the customer data. For example, you might want to analyze only the baskets that contain a specific item, or to analyze the demographics of customers who have not purchased anything in a certain period.

Analysis Services provides the ability to filter the data that is used in a mining model. This feature is useful because you do not need to set up a new data source view to use different data. In the Basic Data Mining Tutorial, you learned how to filter data from a flat table by applying conditions to the case table. In this task, you create a filter that applies to a nested table.

If your data source view contains a case table and a nested table, like the data source view used in the Association model, you can filter on values from the case table, the presence or absence of a value in the nested table, or some combination of both.

In this task, you will first make a copy of the Association model and then add the IncomeGroup and Region attributes to the new related model, so that you can filter on those attributes in the case table.

To create and modify a copy of the Association model

  1. In the Mining Models tab of SQL Server Data Tools (SSDT), right-click the Association model, and select New Mining Model.

  2. For Model Name, type Association Filtered. For Algorithm Name, select Microsoft Association Rules. Click OK.

  3. In the column for the Association Filtered model, click the IncomeGroup row and change the value from Ignore to Input.

Next, you will create a filter on the case table in the new association model. The filter will pass to the model only the customers in the target region or with the target income level. Then, you will add a second set of filter conditions to specify that the model uses only customers whose shopping baskets contained at least one item.

To add a filter to a mining model

  1. In the Mining Models tab, right-click the model Association Filtered, and select Set Model Filter.

  2. In the Model Filter dialog box, click the top row in the grid, in the Mining Structure Column text box.

  3. In the Mining Structure Column text box, select IncomeGroup.

    The icon at the left side of the text box changes to indicate that the selected item is a column.

  4. Click the Operator text box and select the = operator from the list.

  5. Click the Value text box, and type High in the box.

  6. Click the next row in the grid.

  7. Click the AND/OR text box in the next row of the grid and select OR.

  8. In the Mining Structure Column text box, select IncomeGroup. In the Value text box, type Moderate.

    The filter condition that you created is automatically added to the Expression text box, and should appears as follows:

    [IncomeGroup] = 'High' OR [IncomeGroup] = 'Moderate'

  9. Click the next row in the grid, leaving the operator as the default, AND.

  10. For Operator, leave the default value, Contains. Click the Value text box.

  11. In the Filter dialog box, in the first row under Mining Structure Column, select Model.

  12. For Operator, select IS NOT NULL. Leave the Value text box blank. Click OK.

    The filter condition in the Expression text box of the Model Filter dialog box is automatically updated to include the new condition on the nested table. The completed expression is as follows:

    [IncomeGroup] = 'High' OR [IncomeGroup] = 'Moderate' AND EXISTS SELECT * FROM [vAssocSeqLineItems] WHERE [Model] <> NULL).

  13. Click OK.``

To enable drillthrough and to process the filtered model

  1. In the Mining Models tab, right-click the Association Filtered model, and select Properties.

  2. Change the AllowDrillThrough property to True.

  3. Right-click the Association Filtered mining model, and select Process Model.

  4. Click Yes in the error message to deploy the new model to the Analysis Services database.

  5. In the Process Mining Structure dialog box, click Run.

  6. When processing is complete click Close to exit the Process Progress dialog box, and click Close again to exit the Process Mining Structure dialog box.

You can verify by using the Microsoft Generic Content Tree viewer and looking at the value for NODE_SUPPORT that the filtered model contains fewer cases than the original model.

The nested table filter that you just created checks only for the presence of at least one row in the nested table; however, you can also create filter conditions that check for the presence of specific products. For example, you could create the following filter:

[IncomeGroup] = 'High' AND  
 EXISTS (SELECT * FROM [<nested table name>] WHERE [Model] = 'Water Bottle' )   

This statement means that you are restricting the customers from the case table to only those who have purchased a water bottle. However, because the number of nested table attributes is potentially unlimited, Analysis Services does not supply a list of possible values from which to select. Instead, you must type the exact value.

You can click Edit Query to manually change the filter expression. However, if you change any part of a filter expression manually, the grid will be disabled and thereafter you must work with the filter expression in text edit mode only. To restore grid editing mode, you must clear the filter expression and start over.

System_CAPS_ICON_warning.jpg Warning

You cannot use the LIKE operator in a nested table filter.

Predicting Associations (Intermediate Data Mining Tutorial)

Model Filter Syntax and Examples (Analysis Services - Data Mining)
Filters for Mining Models (Analysis Services - Data Mining)