How to connect Bitbucket and Google Cloud BigQuery (REST)
Create a New Scenario to Connect Bitbucket and Google Cloud BigQuery (REST)
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Bitbucket, triggered by another scenario, or executed manually (for testing purposes). In most cases, Bitbucket or Google Cloud BigQuery (REST) will be your first step. To do this, click "Choose an app," find Bitbucket or Google Cloud BigQuery (REST), and select the appropriate trigger to start the scenario.

Add the Bitbucket Node
Select the Bitbucket node from the app selection panel on the right.


Bitbucket

Configure the Bitbucket
Click on the Bitbucket node to configure it. You can modify the Bitbucket URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Cloud BigQuery (REST) Node
Next, click the plus (+) icon on the Bitbucket node, select Google Cloud BigQuery (REST) from the list of available apps, and choose the action you need from the list of nodes within Google Cloud BigQuery (REST).


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Authenticate Google Cloud BigQuery (REST)
Now, click the Google Cloud BigQuery (REST) node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud BigQuery (REST) settings. Authentication allows you to use Google Cloud BigQuery (REST) through Latenode.
Configure the Bitbucket and Google Cloud BigQuery (REST) Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Bitbucket and Google Cloud BigQuery (REST) Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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Trigger on Webhook
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Save and Activate the Scenario
After configuring Bitbucket, Google Cloud BigQuery (REST), and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Bitbucket and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Bitbucket and Google Cloud BigQuery (REST) (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Bitbucket and Google Cloud BigQuery (REST)
Bitbucket + Google Cloud BigQuery (REST) + Slack: When a new commit is made to a Bitbucket repository, the commit data is inserted into a Google Cloud BigQuery table for analysis. Slack then notifies a channel about the new commit.
Google Cloud BigQuery (REST) + Bitbucket + Jira: When a new row is added to a BigQuery table (representing an error log), a Jira issue is automatically created in a specified Bitbucket project for debugging purposes.
Bitbucket and Google Cloud BigQuery (REST) integration alternatives

About Bitbucket
Automate code deployments and issue tracking by connecting Bitbucket to Latenode. Trigger workflows on commit events, automatically update project management tools, and send notifications. Latenode provides a visual editor, affordable scaling, and custom JS nodes for complex branching and data transformation. Streamline your DevOps pipeline with flexible automation.
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About Google Cloud BigQuery (REST)
Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.
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See how Latenode works
FAQ Bitbucket and Google Cloud BigQuery (REST)
How can I connect my Bitbucket account to Google Cloud BigQuery (REST) using Latenode?
To connect your Bitbucket account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Bitbucket and click on "Connect".
- Authenticate your Bitbucket and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze Bitbucket commit data in BigQuery?
Yes, you can! Latenode simplifies data transfer, letting you analyze commit frequency and code changes in BigQuery for valuable insights and reporting. Leverage Latenode's no-code blocks for easy integration.
What types of tasks can I perform by integrating Bitbucket with Google Cloud BigQuery (REST)?
Integrating Bitbucket with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automating data backups from Bitbucket repositories to BigQuery.
- Tracking code commit frequency and author contributions in BigQuery.
- Building custom dashboards in BigQuery based on Bitbucket activity.
- Analyzing project metadata and issue resolution times from Bitbucket.
- Creating alerts based on code changes or repository events using BigQuery.
CanItriggerBigQueryupdatesbasedonBitbucketeventsinLatenode?
Yes, you can. Latenode enables real-time updates to BigQuery based on Bitbucket events like commits, pull requests, and issue changes. Use Javascript steps to customize data transforms.
Are there any limitations to the Bitbucket and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data loading from Bitbucket to BigQuery may take time for large repositories.
- Complex data transformations may require JavaScript coding within Latenode.
- API rate limits on either Bitbucket or BigQuery can affect workflow execution speed.