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

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Authenticate AI Agent
Now, click the AI Agent node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your AI Agent settings. Authentication allows you to use AI Agent through Latenode.
Configure the Google Cloud BigQuery and AI Agent 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 AI Agent 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 Cloud BigQuery, AI Agent, 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 AI Agent integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and AI Agent (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 AI Agent
Google Cloud BigQuery + AI Agent + Slack: When new data is available in BigQuery, an AI Agent analyzes it and posts a summary of insights to a specified Slack channel.
Google Cloud BigQuery + AI Agent + Gmail: When new customer feedback data is available in BigQuery, an AI Agent analyzes the data and drafts a personalized Gmail response. The draft can then be reviewed and sent.
Google Cloud BigQuery and AI Agent 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 AI Agent
Use AI Agent in Latenode to automate content creation, data analysis, or customer support. Configure agents with prompts, then integrate them into workflows. Unlike standalone solutions, Latenode lets you connect AI to any app, scale automatically, and customize with code where needed.
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See how Latenode works
FAQ Google Cloud BigQuery and AI Agent
How can I connect my Google Cloud BigQuery account to AI Agent using Latenode?
To connect your Google Cloud BigQuery account to AI Agent 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 AI Agent accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze BigQuery data with AI for sentiment analysis?
Yes, you can! Latenode simplifies combining Google Cloud BigQuery data with AI Agent's processing. Gain instant sentiment insights from your data without complex code.
What types of tasks can I perform by integrating Google Cloud BigQuery with AI Agent?
Integrating Google Cloud BigQuery with AI Agent allows you to perform various tasks, including:
- Automating sentiment analysis on large datasets stored in Google Cloud BigQuery.
- Generating summaries of key trends and insights from BigQuery data using AI.
- Creating AI-driven reports based on BigQuery data and schedule their delivery.
- Building predictive models based on historical BigQuery data.
- Enriching BigQuery data with AI-generated tags and classifications.
Can I transform data before AI analysis in Latenode?
Yes, Latenode's no-code blocks and JavaScript steps easily transform data before sending it to AI Agent for efficient processing.
Are there any limitations to the Google Cloud BigQuery and AI Agent integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large datasets might require optimization for efficient AI processing.
- AI Agent credits are consumed per transaction, impacting workflow costs.
- Real-time data streaming from Google Cloud BigQuery has latency.