Create a New Relational Mining Structure
Applies to: 
SQL Server 2019 and earlier Analysis Services 
Azure Analysis Services
Fabric/Power BI Premium
Important
Data mining was deprecated in SQL Server 2017 Analysis Services and now discontinued in SQL Server 2022 Analysis Services. Documentation is not updated for deprecated and discontinued features. To learn more, see Analysis Services backward compatibility.
Use the Data Mining Wizard to create a new mining structure, using data from a relational database or other source, and then save the structure and any related models to a Microsoft SQL Server SQL Server Analysis Services database.
To create a relational mining structure
In Solution Explorer, right-click the Mining Structures folder in an SQL Server Analysis Services project, and then click New Mining Structure.
The Data Mining Wizard opens.
On the Welcome to the Data Mining Wizard page, click Next.
On the Select the Definition Method page, select From existing relational database or data warehouse, and then click Next.
On the Select the Data Mining Technique page, select the data mining algorithm that you want to use, and then click Next.
For more information about data mining algorithms, see Data Mining Algorithms (Analysis Services - Data Mining).
On the Select Data Source View page, under Available data source views, click the data source view that you want to use, and then click Next.
For more information about creating a data source view, see Data Source Views in Multidimensional Models.
On the Specify Table Types page, under Input tables, select a case table and a nested table.
On the Specify the Training Data page, under Mining model structure, select the key, input, and predictable columns.
After you select the predictable column, you can click the Suggest button to open the Suggest Related Columns dialog box. You can accept the suggested columns by clicking OK in this dialog box to include the selected columns in the mining structure, or you can change the selections in the Input column first, and then click OK. To ignore the suggestions, click Cancel.
Click Next.
On the Specify Columns' Content and Data Type page, under Mining model structure, you can adjust the content type and data type for each column.
Note
You can click Detect to automatically detect whether a column contains continuous or discrete data. After you click this button, the column content and data types will be updated in the Content Type and Data Type columns. For more information about content types and data types, see Content Types (Data Mining) and Data Types (Data Mining).
Click Next.
On the Completing the Wizard page, provide a name for the mining structure and the related initial mining model that will be created, and then click Finish.