Connect to and Visualize Live Bitbucket Data in Tableau Prep

Tableau is a visual analytics platform transforming the way businesses use data to solve problems. When paired with the CData Tableau Connector for Bitbucket, you can easily get access to live Bitbucket data within Tableau Prep. This article shows how to connect to Bitbucket in Tableau Prep and build a simple chart.

The CData Tableau Connectors enable high-speed access to live Bitbucket data in Tableau. Once you install the connector, you simply authenticate with Bitbucket and you can immediately start building responsive, dynamic visualizations and dashboards. By surfacing Bitbucket data using native Tableau data types and handling complex filters, aggregations, & other operations automatically, CData Tableau Connectors grant seamless access to Bitbucket data.

NOTE: The CData Tableau Connectors support Tableau Prep Builder 2020.4.1 or higher. If you are using an older version of Tableau Prep Builder, you will need to use the CData JDBC Driver.

Install the CData Tableau Connector

When you install the CData Tableau Connector for Bitbucket, the installer should copy the TACO and JAR files to the appropriate directories. If your data source does not appear in the connection steps below, you will need to copy two files:

1. Copy the TACO file (cdata.bitbucket.taco) found in the lib folder of the connector's installation location (C:\Program Files\CData\CData Tableau Connector for Bitbucket 20XX\lib on Windows) to the Tableau Prep Builder repository:
   • Windows: C:\Users\[Windows User]\Documents\My Tableau Prep Repository\Connectors
   • MacOS: /Users//Documents/My Tableau Prep Repository/Connectors
2. Copy the JAR file (cdata.tableau.bitbucket.jar) found in the same lib folder to the Tableau drivers directory, typically [Tableau installation location]\Drivers.

Connect to Bitbucket in Tableau Prep Builder

Open Tableau Prep Builder and click "Connect to Data" and search for "Bitbucket by CData." Configure the connection and click "Sign In."

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.

👁 Configuring the Connector (Sage Intacct is shown)

Discover and Prep Data

Drag the tables and views you wish to work with onto the canvas. You can include multiple tables.

👁 Selecting table(s)

Data Cleansing & Filtering

To further prepare the data, you can implement filters, remove duplicates, modify columns and more.

1. Start by clicking on the plus next to your table and selecting the Clean Step option. 👁 Adding a Clean Step
   
2. Select the field values to filter by. As you select values, you can see how your selections impact other fields. 👁 Selecting test entries (Sage Intacct is shown).
   
3. Opt to "Keep Only" or "Exclude" entries with your select values and the data changes in response. 👁 Excluding selected entries (Sage Intacct is shown).
   

Data Joins and Unions

Data joining involves combining data from two or more related tables based on a common field or key.

1. To join multiple tables, drag a related table next to an existing table in the canvas and place it in the Join box. 👁 Joining two tables (Sage Intacct is shown).
   
2. Select the foreign keys that exist in both tables. 👁 Setting the joining fields/columns (Sage Intacct is shown).
   

Exporting Prepped Data

After you perform any cleansing, filtering, transformations, and joins, you can export the data for visualization in Tableau.

1. Add any other needed transformations then insert an Output node at the end of the flow.
2. Configure the node to save to a file in the format of your choice. 👁 Saving the results (Sage Intacct is shown).
   

Once the output data is saved, you can work with it in Tableau, just like you would any other file source.

Using the CData Tableau Connector for Bitbucket with Tableau Prep Builder, you can easily join, cleanse, filter, and aggregate Bitbucket data for visualizations and reports in Tableau. Download a free, 30-day trial and get started today.