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

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

OpenAI Vision
Configure the OpenAI Vision
Click on the OpenAI Vision node to configure it. You can modify the OpenAI Vision 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 OpenAI Vision 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 OpenAI Vision 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 OpenAI Vision 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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AI Anthropic Claude 3
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Trigger on Webhook
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Save and Activate the Scenario
After configuring OpenAI Vision, 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 OpenAI Vision and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between OpenAI Vision 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 OpenAI Vision and Google Cloud BigQuery (REST)
Google Sheets + Google Cloud BigQuery (REST) + Slack: When a new row is added to a Google Sheet, the data is inserted into a BigQuery table. If specific criteria are met, a Slack message is sent to a designated channel to notify the team about potential anomalies.
Google Sheets + Google Cloud BigQuery (REST) + Slack: When a new row is added to a Google Sheet, the data is inserted into a BigQuery table. A query job is then run on the table and its results are sent to Slack.
OpenAI Vision and Google Cloud BigQuery (REST) integration alternatives
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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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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FAQ OpenAI Vision and Google Cloud BigQuery (REST)
How can I connect my OpenAI Vision account to Google Cloud BigQuery (REST) using Latenode?
To connect your OpenAI Vision account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select OpenAI Vision and click on "Connect".
- Authenticate your OpenAI Vision and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze image data and store insights?
Yes, you can! Latenode allows no-code automation, so you can automatically analyze images with OpenAI Vision, then store the extracted insights in Google Cloud BigQuery (REST) for further analysis.
What types of tasks can I perform by integrating OpenAI Vision with Google Cloud BigQuery (REST)?
Integrating OpenAI Vision with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automatically extract text from images and store it in a database.
- Analyze product images for quality control and log results.
- Process visual data to identify trends and populate dashboards.
- Categorize images based on content and record the classifications.
- Monitor social media images for brand mentions and store findings.
Can I use JavaScript to transform data between the two apps?
Yes! Latenode supports JavaScript, allowing complex data transformations between OpenAI Vision and Google Cloud BigQuery (REST) beyond simple field mapping.
Are there any limitations to the OpenAI Vision and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large volumes of image data can impact workflow execution time.
- Complex data transformations may require JavaScript coding.
- Google Cloud BigQuery (REST) costs apply based on usage volume.