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

Add the Google Chat Node
Select the Google Chat node from the app selection panel on the right.

Google Chat
Configure the Google Chat
Click on the Google Chat node to configure it. You can modify the Google Chat 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 Chat 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 Chat 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 Chat 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Chat, 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 Chat and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Google Chat 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 Chat and Google Cloud BigQuery (REST)
Google Chat + Google Cloud BigQuery (REST) + Google Sheets: When a new message is posted in Google Chat, the message details are added as a new row in Google Cloud BigQuery. Then, Google Sheets retrieves data from BigQuery and displays summarized statistics.
Google Cloud BigQuery (REST) + Google Chat + Slack: When a new row is added to a BigQuery table, indicating a critical error, a message is sent to a Google Chat space, and a backup notification is sent to a Slack channel.
Google Chat and Google Cloud BigQuery (REST) integration alternatives
About Google Chat
Use Google Chat in Latenode for automated notifications & alerts. Trigger messages based on events in other apps, like new database entries or payment confirmations. Centralize alerts and status updates across services within a single, scalable Latenode workflow. Add custom logic and AI for smart notifications.
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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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See how Latenode works
FAQ Google Chat and Google Cloud BigQuery (REST)
How can I connect my Google Chat account to Google Cloud BigQuery (REST) using Latenode?
To connect your Google Chat account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Chat and click on "Connect".
- Authenticate your Google Chat and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I log Google Chat messages in BigQuery?
Yes, you can log Google Chat messages in BigQuery! Latenode's visual editor makes this easy to set up. Centralize data and gain deeper insights without complex coding.
What types of tasks can I perform by integrating Google Chat with Google Cloud BigQuery (REST)?
Integrating Google Chat with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Archive Google Chat messages for compliance and auditing purposes.
- Analyze chat data to identify trends and improve team communication.
- Create custom reports based on chat activity using BigQuery's powerful querying.
- Trigger automated alerts in Google Chat based on BigQuery data analysis.
- Build dashboards visualizing chat data alongside other business metrics.
Can I use AI to analyze Google Chat data before saving it to BigQuery?
Yes! With Latenode, integrate AI steps to analyze sentiment or extract entities from Google Chat messages before saving them to BigQuery.
Are there any limitations to the Google Chat and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers may be subject to Google API rate limits.
- Complex data transformations might require custom JavaScript code.
- Initial setup requires familiarity with both Google Chat and BigQuery APIs.