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

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

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

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Authenticate OpenAI Responses
Now, click the OpenAI Responses node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OpenAI Responses settings. Authentication allows you to use OpenAI Responses through Latenode.
Configure the Google Cloud BigQuery and OpenAI Responses 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 and OpenAI Responses 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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AI Anthropic Claude 3
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OpenAI Responses
Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery, OpenAI Responses, 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 and OpenAI Responses integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and OpenAI Responses (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 and OpenAI Responses
Google Cloud BigQuery + OpenAI Responses + Slack: Analyze data in BigQuery. Use OpenAI to summarize the findings and insights. Post the summarized insights to a designated Slack channel for team awareness.
OpenAI Responses + Google Cloud BigQuery + Google Sheets: When OpenAI generates content, store it in BigQuery. Subsequently, track the performance or characteristics of that stored content by recording data associated with it in Google Sheets.
Google Cloud BigQuery and OpenAI Responses integration alternatives
About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
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About OpenAI Responses
Need AI-powered text generation? Use OpenAI Responses in Latenode to automate content creation, sentiment analysis, and data enrichment directly within your workflows. Streamline tasks like generating product descriptions or classifying customer feedback. Latenode lets you chain AI tasks with other services, adding logic and routing based on results – all without code.
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See how Latenode works
FAQ Google Cloud BigQuery and OpenAI Responses
How can I connect my Google Cloud BigQuery account to OpenAI Responses using Latenode?
To connect your Google Cloud BigQuery account to OpenAI Responses on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery and click on "Connect".
- Authenticate your Google Cloud BigQuery and OpenAI Responses accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze BigQuery data with OpenAI for sentiment?
Yes, you can! Latenode lets you automate sentiment analysis using OpenAI on your BigQuery datasets, providing actionable insights with zero code and scheduled workflows.
What types of tasks can I perform by integrating Google Cloud BigQuery with OpenAI Responses?
Integrating Google Cloud BigQuery with OpenAI Responses allows you to perform various tasks, including:
- Generate summaries of customer feedback stored in BigQuery.
- Create AI-powered reports using BigQuery data.
- Enrich BigQuery datasets with insights from OpenAI models.
- Automate data cleaning and validation using AI.
- Classify and categorize BigQuery data using OpenAI.
How does Latenode handle BigQuery data security?
Latenode employs robust security measures, including encryption and access controls, to safeguard your BigQuery data during integration and processing.
Are there any limitations to the Google Cloud BigQuery and OpenAI Responses integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large datasets may require optimized queries for efficient processing.
- OpenAI usage is subject to their rate limits and API usage policies.
- Complex data transformations might require custom JavaScript code.