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How to connect Google Vertex AI and Google Cloud BigQuery (REST)
Create a New Scenario to Connect Google Vertex AI 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 Google Vertex AI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Vertex AI or Google Cloud BigQuery (REST) will be your first step. To do this, click "Choose an app," find Google Vertex AI or Google Cloud BigQuery (REST), and select the appropriate trigger to start the scenario.
Add the Google Vertex AI Node
Select the Google Vertex AI node from the app selection panel on the right.
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Configure the Google Vertex AI
Click on the Google Vertex AI node to configure it. You can modify the Google Vertex AI 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 Google Vertex AI 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 Google Vertex AI 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 Google Vertex AI 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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Save and Activate the Scenario
After configuring Google Vertex AI, 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 Google Vertex AI and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Google Vertex AI 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 Google Vertex AI and Google Cloud BigQuery (REST)
Google Cloud BigQuery (REST) + Google Vertex AI + Google Sheets: A new table in BigQuery triggers a data analysis job in Vertex AI using Gemini. The analysis results are then inserted into a Google Sheet for visualization and reporting.
Google Cloud BigQuery (REST) + Google Vertex AI + Slack: When new data is available in BigQuery, execute a query job. The result is then passed to Vertex AI to detect anomalies and if any found, the data team will be alerted via Slack.
Google Vertex AI and Google Cloud BigQuery (REST) integration alternatives
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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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 Google Vertex AI and Google Cloud BigQuery (REST)
How can I connect my Google Vertex AI account to Google Cloud BigQuery (REST) using Latenode?
To connect your Google Vertex AI account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Vertex AI and click on "Connect".
- Authenticate your Google Vertex AI and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze AI model outputs stored in BigQuery?
Yes! Latenode lets you automate analyzing Google Vertex AI model outputs in Google Cloud BigQuery (REST), then trigger actions based on insights. No-code makes it simple.
What types of tasks can I perform by integrating Google Vertex AI with Google Cloud BigQuery (REST)?
Integrating Google Vertex AI with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automating data ingestion from Google Vertex AI into Google Cloud BigQuery (REST).
- Building real-time dashboards of model performance metrics.
- Creating automated alerts based on anomalies detected in Google Vertex AI outputs.
- Enriching existing Google Cloud BigQuery (REST) datasets with Google Vertex AI predictions.
- Orchestrating complex data pipelines using AI insights and stored data.
Can I use JavaScript to transform data between Vertex AI and BigQuery?
Yes, Latenode’s JavaScript blocks let you transform data between Google Vertex AI and Google Cloud BigQuery (REST) with custom logic and code.
Are there any limitations to the Google Vertex AI and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data schema setup must be configured manually.
- Complex data transformations may require custom JavaScript coding.
- Rate limits of both Google Vertex AI and Google Cloud BigQuery (REST) still apply.
