Prepare, Blend, and Analyze Bitbucket Data in Alteryx Designer

The CData ODBC Driver for Bitbucket enables access to live data from Bitbucket under the ODBC standard, allowing you work with Bitbucket data in a wide variety of BI, reporting, and ETL tools and directly, using familiar SQL queries. This article shows how to connect to Bitbucket data using an ODBC connection in Alteryx Designer to perform self-service BI, data preparation, data blending, and advanced analytics.

The CData ODBC drivers offer unmatched performance for interacting with live Bitbucket data in Alteryx Designer due to optimized data processing built into the driver. When you issue complex SQL queries from Alteryx Designer 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 Alteryx data field types.

Connect to Bitbucket Data

1. If you have not already done so, provide values for the required connection properties in the data source name (DSN). You can configure the DSN using the built-in Microsoft ODBC Data Source Administrator. This is also the last step of the driver installation. See the "Getting Started" chapter in the Help documentation for a guide to using the Microsoft ODBC Data Source Administrator to create and configure a DSN.
   
   

   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.

2. Open Alteryx Designer and create a new workflow.
3. Drag and drop a new input data tool onto the workflow.
4. Click the drop down under Connect a File or Database and select the Data sources tab.
5. Navigate tot he end of the page and click on "ODBC" under "Generic connection"
6. Select the DSN (CData Bitbucket Source) that you configured for use in Alteryx.
7. In the wizard that opens, drag, and drop the table to be queried in the "Query Builder box." Select the fields by checking the boxes that you wish to include in your query. 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 client-side by the CData SQL engine embedded in the connector.

If you wish to further customize your dataset, you can open the SQL Editor and modify the query manually, adding clauses, aggregations, and other operations to ensure that you are retrieving exactly the Bitbucket data you want .

With the query defined, you are ready to work with Bitbucket data in Alteryx Designer.

Perform Self-Service Analytics on Bitbucket Data

You are now ready to create a workflow to prepare, blend, and analyze Bitbucket data. The CData ODBC Driver performs dynamic metadata discovery, presenting data using Alteryx data field types and allowing you to leverage the Designer's tools to manipulate data as needed and build meaningful datasets. In the example below, you will cleanse and browse data.

1. Add a data cleansing tool to the workflow and check the boxes in Replace Nulls to replace null text fields with blanks and replace null numeric fields with 0. You can also check the box in Remove Unwanted Characters to remove leading and trailing whitespace.
2. Add a browse data tool to the workflow.
3. Click to run the workflow (CTRL+R).
4. Browse your cleansed Bitbucket data in the results view.

Thanks to built-in, high-performance data processing, you will be able to quickly cleanse, transform, and/or analyze your Bitbucket data with Alteryx.