Connect to Live Bitbucket Data in MicroStrategy through CData Connect AI

MicroStrategy is an analytics and mobility platform that enables data-driven innovation. When you pair MicroStrategy with CData Connect AI, you gain database-like access to live Bitbucket data from MicroStrategy, expanding your reporting and analytics capabilities. In this article, we walk through connecting to Bitbucket in Connect AI and connecting to Connect AI in MicroStrategy to create a simple visualization of Bitbucket data.

As a cloud-based integration platform, Connect AI is ideal for working with cloud-based BI and analytics tools. With no servers to configure or data proxies to set up, you can simply use the web-based UI to create a live connection to Bitbucket and connect from MicroStrategy to start performing analytics based on live Bitbucket data.

Configure Bitbucket Connectivity for Microstrategy

Connectivity to Bitbucket from Microstrategy is made possible through CData Connect AI. To work with Bitbucket data from Microstrategy, we start by creating and configuring a Bitbucket connection.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Bitbucket" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Bitbucket.

   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.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Bitbucket Connection page and update the User-based permissions.

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Bitbucket data from MicroStrategy.

Connect to and Visualize Bitbucket Data Using MicroStrategy

You can connect to Bitbucket in MicroStrategy by adding a data source based on the native SQL Server functionality. Once you have created a data source, you can build dynamic visualizations of Bitbucket data in MicroStrategy.

1. Open MicroStrategy and select your account.
2. Click Add External Data, select Databases, and use Select Tables as the Import Option.
3. In the Import from Tables wizard, click to add a new Data Source.
4. Select "SQL Server" in the Database menu and select "SQL Server 2017" in the Version menu.
5. Sat the connection properties as follows:
   • Server Name: tds.cdata.com
   • Port Number: 14333
   • Database Name: the name of your Bitbucket connection (e.g. Bitbucket1)
   • User: a Connect AI user
   • Password: the PAT for your Connect AI user
   • Data Source Name: a name for the new external data source, like "CData Cloud Bitbucket"
6. Expand the menu for the new data source and choose "Edit Catalog Options"
7. Edit the "SQL statement retrieve columns ..." query to include TABLE_SCHEMA = '#?Schema_Name?#' in the WHERE clause, and click Apply and then OK (the complete query is below).
   
   

   SELECT DISTINCT 
     TABLE_SCHEMA NAME_SPACE, 
     TABLE_NAME TAB_NAME, 
     COLUMN_NAME COL_NAME, 
     (CASE 
       WHEN 
         (DATA_TYPE LIKE '%char' AND (CHARACTER_SET_NAME='utf8' OR CHARACTER_SET_NAME='usc2')) 
       THEN 
         CONCAT('a',DATA_TYPE) 
       ELSE 
         DATA_TYPE 
     END) DATA_TYPE, 
     CHARACTER_MAXIMUM_LENGTH DATA_LEN, 
     NUMERIC_PRECISION DATA_PREC, 
     NUMERIC_SCALE DATA_SCALE 
   FROM 
     INFORMATION_SCHEMA.COLUMNS 
   WHERE 
     TABLE_NAME 
   IN 
     (#TABLE_LIST#) AND TABLE_SCHEMA='#?Schema_Name?#' 
   ORDER BY 
     1,2,3
   

8. Select the new data source and select the Namespace that corresponds to your virtual Bitbucket database (like Bitbucket1).
9. Drag tables into the pane to insert then. Note: Since we create a live connection, we can insert whole tables and utilize the filtering and aggregation features native to the MicroStrategy products to customize our datasets.
10. Click Finish, choose the option to connect live, save the query, and choose the option to create a new dossier. Live connections are possible and effective, thanks to high-performance data processing native to CData Connect AI.
11. Choose a visualization, choose fields to display, and apply any filters to create a new visualization of Bitbucket data. Data types are discovered automatically through dynamic metadata discovery. Where possible, the complex queries generated by the filters and aggregations will be pushed down to Bitbucket, while any unsupported operations (which can include SQL functions and JOIN operations) will be managed by the CData SQL engine embedded in Connect AI.
12. Once you have finished configuring the dossier, click File -> Save.

Using CData Connect AI with MicroStrategy, you can easily create robust visualizations and reports on Bitbucket data. For more information on connecting to Bitbucket (and more than 100 other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Bitbucket data in MicroStrategy.