How to connect Google Cloud BigQuery (REST) and Code
Create a New Scenario to Connect Google Cloud BigQuery (REST) and Code
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 Google Cloud BigQuery (REST), triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery (REST) or Code will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Code, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery (REST) Node
Select the Google Cloud BigQuery (REST) node from the app selection panel on the right.

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

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Authenticate Code
Now, click the Code node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Code settings. Authentication allows you to use Code through Latenode.
Configure the Google Cloud BigQuery (REST) and Code 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 Google Cloud BigQuery (REST) and Code 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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Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), Code, 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 Google Cloud BigQuery (REST) and Code integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Code (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud BigQuery (REST) and Code
Google Cloud BigQuery (REST) + Code + Google Sheets: Query data in BigQuery using a REST request. Use a JavaScript code block to analyze the results. Finally, write the processed data to a Google Sheet for reporting and analysis.
Code + Google Cloud BigQuery (REST) + Slack: Schedule code execution to query BigQuery, then post a summary of the queried data to a designated Slack channel for team awareness.
Google Cloud BigQuery (REST) and Code integration alternatives
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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About Code
Need custom logic within your Latenode workflows? Code lets you add JavaScript snippets and NPM modules directly into your automation flows. Transform data, handle complex calculations, and connect to unsupported APIs. Latenode makes it easy to manage code alongside no-code steps, ensuring scalability and maintainability.
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See how Latenode works
FAQ Google Cloud BigQuery (REST) and Code
How can I connect my Google Cloud BigQuery (REST) account to Code using Latenode?
To connect your Google Cloud BigQuery (REST) account to Code on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery (REST) and click on "Connect".
- Authenticate your Google Cloud BigQuery (REST) and Code accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate data transformations using BigQuery data in Code?
Yes, you can. Latenode allows seamless data transfer between Google Cloud BigQuery (REST) and Code for complex transformations. Leverage JavaScript blocks for custom logic and advanced data manipulation.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Code?
Integrating Google Cloud BigQuery (REST) with Code allows you to perform various tasks, including:
- Automating data validation processes using custom JavaScript code.
- Generating reports based on BigQuery data using server-side code.
- Creating custom APIs from BigQuery data using Code's serverless functions.
- Transforming data formats before loading them into Google Cloud BigQuery (REST).
- Building dynamic dashboards fed by BigQuery data, enhanced via Code.
HowsecureistheGoogleCloudBigQuery(REST)integrationonLatenode?
Latenode employs secure authentication and encryption protocols for Google Cloud BigQuery (REST), ensuring data integrity and compliance with industry security standards.
Are there any limitations to the Google Cloud BigQuery (REST) and Code integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers from Google Cloud BigQuery (REST) may impact workflow execution time.
- Complex JavaScript code in Code blocks may require debugging.
- Google Cloud BigQuery (REST) API usage is subject to Google's rate limits.