How to connect Google Cloud BigQuery (REST) and OpenAI Vision
Create a New Scenario to Connect Google Cloud BigQuery (REST) and OpenAI Vision
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 OpenAI Vision will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or OpenAI Vision, 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 OpenAI Vision Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select OpenAI Vision from the list of available apps, and choose the action you need from the list of nodes within OpenAI Vision.

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Authenticate OpenAI Vision
Now, click the OpenAI Vision node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OpenAI Vision settings. Authentication allows you to use OpenAI Vision through Latenode.
Configure the Google Cloud BigQuery (REST) and OpenAI Vision 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 OpenAI Vision 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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OpenAI Vision
Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), OpenAI Vision, 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 OpenAI Vision integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and OpenAI Vision (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 OpenAI Vision
Google Cloud BigQuery (REST) + OpenAI Vision + Slack: Analyze data in BigQuery, use it to select an image, have Vision analyze the image, then post insights to Slack.
Google Sheets + Google Cloud BigQuery (REST) + OpenAI Vision: When a new row is added to a Google Sheet, analyze related image in BigQuery, and store the results in the same Google Sheet.
Google Cloud BigQuery (REST) and OpenAI Vision 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 OpenAI Vision
Use OpenAI Vision in Latenode to automate image analysis tasks. Detect objects, read text, or classify images directly within your workflows. Integrate visual data with databases or trigger alerts based on image content. Latenode's visual editor and flexible integrations make it easy to add AI vision to any process. Scale automations without per-step pricing.
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See how Latenode works
FAQ Google Cloud BigQuery (REST) and OpenAI Vision
How can I connect my Google Cloud BigQuery (REST) account to OpenAI Vision using Latenode?
To connect your Google Cloud BigQuery (REST) account to OpenAI Vision 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 OpenAI Vision accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze images stored in BigQuery using OpenAI Vision?
Yes, you can! Latenode facilitates this by enabling direct data transfer and processing between the apps. This gives instant image insights, automating workflows and boosting productivity.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with OpenAI Vision?
Integrating Google Cloud BigQuery (REST) with OpenAI Vision allows you to perform various tasks, including:
- Automatically tag images stored in BigQuery based on visual content.
- Extract text from images and store the data in BigQuery tables.
- Analyze image sentiment and log results in BigQuery for reporting.
- Detect objects in images and update BigQuery datasets accordingly.
- Generate image descriptions and save them as structured data.
Can I schedule regular BigQuery data updates with OpenAI Vision analysis?
Yes! Latenode lets you schedule workflows, automating BigQuery data analysis and OpenAI Vision processing at desired intervals.
Are there any limitations to the Google Cloud BigQuery (REST) and OpenAI Vision integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large image datasets from BigQuery may require optimized processing for speed.
- Complex vision tasks may consume more OpenAI Vision processing credits.
- Data transfer costs between Google Cloud BigQuery (REST) and OpenAI Vision apply.