Visualize Bitbucket Data in Tableau

The CData ODBC Driver for Bitbucket enables you to access live Bitbucket data in business intelligence tools like Tableau. In this article, you will integrate Bitbucket data into a dashboard that reflects changes to Bitbucket data in real time.

The CData ODBC drivers offer unmatched performance for interacting with live Bitbucket data in Tableau due to optimized data processing built into the driver. When you issue complex SQL queries from Tableau to Bitbucket, the driver pushes supported SQL operations, like filters and aggregations, directly to Bitbucket and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze Bitbucket data using native Tableau data types.

Connect to Bitbucket as an ODBC Data Source

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

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 DSN, 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.

Add Bitbucket Data to a Dashboard

1. Click Connect to Data -> More Servers -> Other Databases (ODBC).
   Select the CData Data Source Name (for example: CData Bitbucket Source).
2. In the Database menu, select CData.
3. In the Table box, enter a table name or click New Custom SQL to enter an SQL query. This article retrieves the Issues table.
4. Drag the table onto the join area. At this point, you can include multiple tables, leveraging the built-in SQL engine to process complex data requests. 👁 A connection to a single table. (Google Sheets is shown.)
   
5. In the Connection menu, select the Live option, so that you skip loading a copy of the data into Tableau and instead work on real-time data. The optimized data processing native to CData ODBC drivers enables unmatched performance in live connectivity.
6. Click the tab for your worksheet. Columns are listed as Dimensions and Measures, depending on the data type. The CData driver discovers data types automatically, allowing you to leverage the powerful data processing and visualization features of Tableau.
7. Drop the Title column in the Dimensions pane onto the dashboard. When you select dimensions, Tableau builds a query to the driver. The results are grouped based on that dimension. In Tableau, the raw query is automatically modified as you select dimensions and measures.

8. Drag the ContentRaw column in the Measures field onto the Detail and Color buttons. Tableau executes the following query:

   SELECT Title, SUM(ContentRaw) FROM Issues GROUP BY Title
   

   When you select a measure, Tableau executes a command to the driver to calculate a summary function, such as SUM, AVG, etc., on the grouped values. The SQL engine (embedded within the driver) is leveraged to process the aggregation of the data, where needed, providing a seamless experience in Tableau, regardless of the data source.

   To change the summary function, open the ContentRaw menu and select the summary you want in the Measure command.

   👁 A simple visualization that shows the latest data.
   

9. You can create other charts using dimensions and measures to build SQL queries visually:

   👁 A dashboard with several visualizations. The SQL query that corresponds to each chart is shown next to the chart. (Google Sheets is shown.)
   

With the CData ODBC Driver for Bitbucket, you get live connectivity to your Bitbucket data, allowing you to build real-time charts, graphs, and more.