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

Add the Facebook Messenger Node
Select the Facebook Messenger node from the app selection panel on the right.


Facebook Messenger

Configure the Facebook Messenger
Click on the Facebook Messenger node to configure it. You can modify the Facebook Messenger 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 Facebook Messenger 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 Facebook Messenger 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 Facebook Messenger 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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AI Anthropic Claude 3
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Google Cloud BigQuery (REST)
Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Facebook Messenger, 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 Facebook Messenger and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Facebook Messenger 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 Facebook Messenger and Google Cloud BigQuery (REST)
Facebook Messenger + Google Cloud BigQuery (REST) + Google Sheets: When a new message is received in Facebook Messenger, extract the relevant survey response and insert it as a new row into a BigQuery table. Then, use Google Sheets to summarize and analyze the data from BigQuery, updating a spreadsheet with key metrics.
Google Cloud BigQuery (REST) + Facebook Messenger + Slack: When a new row is added to a specific table in BigQuery (REST), indicating a critical issue detected by data analysis, send an alert via Facebook Messenger to a specific user. Simultaneously, send a notification to a designated Slack channel to inform the broader team.
Facebook Messenger and Google Cloud BigQuery (REST) integration alternatives

About Facebook Messenger
Connect Facebook Messenger to Latenode to automate customer support or send personalized updates. Build flows to handle inbound messages, trigger actions in other apps, and route conversations intelligently. Use Latenode's visual editor and scripting tools to scale communication workflows with custom logic, without step-based pricing.
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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 Facebook Messenger and Google Cloud BigQuery (REST)
How can I connect my Facebook Messenger account to Google Cloud BigQuery (REST) using Latenode?
To connect your Facebook Messenger account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Facebook Messenger and click on "Connect".
- Authenticate your Facebook Messenger and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze Facebook Messenger data in BigQuery automatically?
Yes, you can! Latenode automates data transfer from Facebook Messenger to Google Cloud BigQuery (REST), enabling analysis and reporting with ease, plus scaling for large datasets.
What types of tasks can I perform by integrating Facebook Messenger with Google Cloud BigQuery (REST)?
Integrating Facebook Messenger with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Storing Facebook Messenger chatbot data for detailed analytics.
- Analyzing customer sentiment from Facebook Messenger conversations.
- Creating personalized marketing campaigns based on message data.
- Tracking support ticket resolution times via Facebook Messenger.
- Building dashboards visualizing key Facebook Messenger metrics.
How secure is Facebook Messenger integration with Google Cloud BigQuery (REST)?
Latenode uses secure authentication and encryption to protect your Facebook Messenger and Google Cloud BigQuery (REST) data during integration.
Are there any limitations to the Facebook Messenger and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by Facebook Messenger may affect data transfer frequency.
- Complex data transformations might require JavaScript coding.
- Historical data migration from Facebook Messenger has size constraints.