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

Add the Google Cloud BigQuery (REST) Node
Select the Google Cloud BigQuery (REST) node from the app selection panel on the right.

Google Cloud BigQuery (REST)
Configure the Google Cloud BigQuery (REST)
Click on the Google Cloud BigQuery (REST) node to configure it. You can modify the Google Cloud BigQuery (REST) URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Tamtam Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select Tamtam from the list of available apps, and choose the action you need from the list of nodes within Tamtam.

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Authenticate Tamtam
Now, click the Tamtam node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Tamtam settings. Authentication allows you to use Tamtam through Latenode.
Configure the Google Cloud BigQuery (REST) and Tamtam 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 (REST) and Tamtam 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 (REST), Tamtam, 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 (REST) and Tamtam integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Tamtam (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 (REST) and Tamtam
Google Cloud BigQuery (REST) + Google Sheets + Tamtam: Analyze data in BigQuery using a query job. Save the query results to a Google Sheet. Then, send a summary of the analysis from the Google Sheet to a Tamtam chat.
Tamtam + Google Cloud BigQuery (REST) + AI GPT Router: When new messages are received in Tamtam, log the message content in a BigQuery table. Use AI GPT Router to process the message and route it to the appropriate team or channel based on the content.
Google Cloud BigQuery (REST) and Tamtam integration alternatives
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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About Tamtam
Use Tamtam in Latenode to automate messaging tasks. Send alerts, notifications, or updates based on triggers from other apps. Build workflows to distribute information automatically. Tamtam integration in Latenode avoids manual message sending, saving time. Plus, customize messaging flows with JS or AI for targeted and personalized comms.
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FAQ Google Cloud BigQuery (REST) and Tamtam
How can I connect my Google Cloud BigQuery (REST) account to Tamtam using Latenode?
To connect your Google Cloud BigQuery (REST) account to Tamtam on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery (REST) and click on "Connect".
- Authenticate your Google Cloud BigQuery (REST) and Tamtam accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I get BigQuery data sent to Tamtam?
Yes, using Latenode, you can automatically send BigQuery data summaries to Tamtam channels. Share key metrics instantly, without manual reporting. Use JavaScript or AI blocks for transformations.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Tamtam?
Integrating Google Cloud BigQuery (REST) with Tamtam allows you to perform various tasks, including:
- Send daily sales reports from BigQuery to a Tamtam channel.
- Alert a Tamtam group when BigQuery data exceeds a threshold.
- Post new BigQuery records to Tamtam for immediate review.
- Trigger workflows based on Tamtam messages to update BigQuery.
- Summarize BigQuery analytics and share them in Tamtam.
How secure is my BigQuery data when integrated with Tamtam?
Latenode uses secure connections and encryption to protect your BigQuery data during integration with Tamtam, adhering to industry best practices for data security.
Are there any limitations to the Google Cloud BigQuery (REST) and Tamtam integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers from BigQuery to Tamtam may experience delays.
- Tamtam's API rate limits can impact the frequency of updates.
- Custom JavaScript transformations require coding expertise.