Build an OLAP Cube in SSAS from Bitbucket Data

SQL Server Analysis Services (SSAS) serves as an analytical data engine employed in decision support and business analytics, offering high-level semantic data models for business reports and client applications like Power BI, Excel, Reporting Services reports, and various data visualization tools. When coupled with the CData ADO.NET Provider for Bitbucket, you gain the capability to generate cubes from Bitbucket data, facilitating more profound and efficient data analysis.

In this article, we will guide you through the process of developing and deploying a multi-dimensional model of Bitbucket data by creating an Analysis Services project in Visual Studio. To proceed, ensure that you have an accessible SSAS instance and have installed the ADO.NET Provider.

Creating a Data Source for Bitbucket

Start by creating a new Analysis Service Multidimensional and Data Mining Project in Visual Studio. Next, create a Data Source for Bitbucket data in the project.

1. In the Solution Explorer, right-click Data Source and select New Data Source.
2. Opt to create a data source based on an existing or new connection and click New.
3. In the Connection Manager, select CData ADO.NET Provider for Bitbucket, enter the necessary connection properties, and click Next.

   For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

   Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

   • Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
   • Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

   Authenticating to Bitbucket

   Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

   Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

   Creating a custom OAuth application

   From your Bitbucket account:

   1. Go to Settings (the gear icon) and select Workspace Settings.
   2. In the Apps and Features section, select OAuth Consumers.
   3. Click Add Consumer.
   4. Enter a name and description for your custom application.
   5. Set the callback URL:
      • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
      • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
   6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
   7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
   8. To save the new custom application, click Save.
   9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.

   When you configure the connection, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

4. Set the impersonation method to Inherit and click Next.
5. Name the data source (CData Bitbucket Source) and click Finish.

Creating a Data Source View

After you create the data source, create the data source view.

1. In the Solution Explorer, right-click Data Source Views and select New Data Source View.
2. Select the data source you just created (CData Bitbucket Source) and click Next.
3. Choose a foreign key match pattern that matches your underlying data source and click Next.
4. Select Bitbucket tables to add to the view and click Next.
5. Name the view and click Finish

Based on the foreign key match scheme, relationships in the underlying data will be automatically detected. You can view (and edit) these relationships by double clicking Data Source View.

Note that adding a secondary data source to the Data Source View is not supported. When working with multiple data sources, SSAS requires both sources to support remote queries via OpenRowset which is unavailable in the ADO.NET Provider.

Creating a Cube for Bitbucket

The last step before you can process the project and deploy Bitbucket data to SSAS is creating the cubes.

1. In the Solution Explorer, right-click Cubes and select New Cube
2. Select "Use existing tables" and click Next.
3. Select the tables that will be used for measure group tables and click Next.
4. Select the measures you want to include in the cube and click Next.
5. Select the dimensions to be created, based on the available tables, and click Next.
6. Review all of your selections and click Finish.

Process the Project

With the data source, data source view, and cube created, you are ready to deploy the cube to SSAS. To configure the target server and database, right-click the project and select properties. Navigate to deployment and configure the Server and Database properties in the Target section.

After configuring the target server and database, right-click the project and select Process. You may need to build and deploy the project as a part of this step. Once the project is built and deployed, click Run in the Process Database wizard.

Now you have an OLAP cube for Bitbucket data in your SSAS instance, ready to be analyzed, reported, and viewed. Get started with a free, 30-day trial of the CData ADO.NET Provider for Bitbucket.