Connect to Bitbucket Data in ACL Analytics
ACL Analytics, part of Diligent HighBond, is a powerful data analysis software primarily used for audit, risk management, and compliance. It enables professionals to examine and analyze large volumes of data to identify anomalies, trends, and potential risks or fraudulent activities.
CData Connect AI offers a dedicated cloud-to-cloud interface for Bitbucket, enabling analytics directly from live Bitbucket data within ACL Analytics, all without the need for data replication to a native database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to Bitbucket. This leverages server-side processing to swiftly deliver the requested Bitbucket data.
Configure Bitbucket Connectivity for ACL Analytics
Connectivity to Bitbucket from ACL Analytics is made possible through CData Connect AI. To work with Bitbucket data from ACL Analytics, we start by creating and configuring a Bitbucket connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Bitbucket" from the Add Connection panel
- Enter the necessary authentication properties to connect to Bitbucket.
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:
- Go to Settings (the gear icon) and select Workspace Settings.
- In the Apps and Features section, select OAuth Consumers.
- Click Add Consumer.
- Enter a name and description for your custom application.
- 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.
- 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.
- Select which permissions to give your OAuth application. These determine what data you can read and write with it.
- To save the new custom application, click Save.
- 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.
- Click Save & Test
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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.
- Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- 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 ACL Analytics.
Connect to Bitbucket from ACL Analytics
The steps below outline connecting to CData Connect AI from ACL Analytics to create a new Bitbucket data source. The CData Connect AI Virtual SQL Server allows you to establish a connection to your data from integration tools that support connections to SQL servers. The Virtual SQL Server mimics the behavior of a traditional SQL server, and it supports a range of query options.
- With your Analytics File open, select 'Import' --> 'Database and application'
- Create a new SQL Server connection
- Set the connection information
- Server: tds.cdata.com
- Port: 14333
- Auth Scheme: Password
- Username: a Connect AI user, for example, [email protected]
- Password: the PAT for the above Connect AI user
- Database: the name of your Bitbucket connection, for example, Bitbucket1
- Click "Test Connection"
- Click "OK"
- You are now ready to work with your Bitbucket data in ACL Analytics!
Live connections to Bitbucket data from your applications
ACL Analytics can now connect to live Bitbucket data directly through Connect AI, allowing you to analyze Bitbucket data without duplicating it.
To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your applications, try CData Connect AI today!