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Enrich data in Google Cloud BigQuery with AI insights from Google Vertex AI. Latenode's visual editor simplifies complex pipelines, while flexible JavaScript nodes and affordable execution costs keep your AI projects scalable.
Connect Google Cloud BigQuery and Google Vertex AI in minutes with Latenode.
Create Google Cloud BigQuery to Google Vertex AI workflow
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Create a New Scenario to Connect Google Cloud BigQuery and Google Vertex AI
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 Google Vertex AI will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Google Vertex AI, 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 Google Vertex AI Node
Next, click the plus (+) icon on the Google Cloud BigQuery node, select Google Vertex AI from the list of available apps, and choose the action you need from the list of nodes within Google Vertex AI.
Google Cloud BigQuery
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Google Vertex AI
Authenticate Google Vertex AI
Now, click the Google Vertex AI node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Vertex AI settings. Authentication allows you to use Google Vertex AI through Latenode.
Configure the Google Cloud BigQuery and Google Vertex AI 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 Google Vertex AI Integration
Use various Latenode nodes to transform data and enhance your integration:
JavaScript
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AI Anthropic Claude 3
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Google Vertex AI
Trigger on Webhook
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Google Cloud BigQuery
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring Google Cloud BigQuery, Google Vertex AI, 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 Google Vertex AI integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Google Vertex AI (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Google Cloud BigQuery + Google Vertex AI + Google Sheets: Analyze data from Google Cloud BigQuery using Google Vertex AI's Gemini model, then save the analysis results to a new row in Google Sheets for reporting and tracking.
Google Cloud BigQuery + Google Vertex AI + Slack: When new data is added to BigQuery, analyze it using Vertex AI. If anomalies are detected, send a message to a designated Slack channel to alert the team.
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 Google Vertex AI
Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.
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How can I connect my Google Cloud BigQuery account to Google Vertex AI using Latenode?
To connect your Google Cloud BigQuery account to Google Vertex AI on Latenode, follow these steps:
Can I train custom models using BigQuery data in Vertex AI?
Yes, you can. Latenode simplifies data transfer and model training, enabling faster iteration & deployment. Leverage no-code blocks, JavaScript & AI to optimize your models.
What types of tasks can I perform by integrating Google Cloud BigQuery with Google Vertex AI?
Integrating Google Cloud BigQuery with Google Vertex AI allows you to perform various tasks, including:
How does Latenode handle large BigQuery datasets efficiently?
Latenode leverages streaming and batch processing, optimized data transfer and scalable infrastructure to process large datasets efficiently.
Are there any limitations to the Google Cloud BigQuery and Google Vertex AI integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: