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

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

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

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Authenticate Google Cloud BigQuery
Now, click the Google Cloud BigQuery 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 settings. Authentication allows you to use Google Cloud BigQuery through Latenode.
Configure the CloudTalk and Google Cloud BigQuery 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 CloudTalk and Google Cloud BigQuery 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 CloudTalk, Google Cloud BigQuery, 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 CloudTalk and Google Cloud BigQuery integration works as expected. Depending on your setup, data should flow between CloudTalk and Google Cloud BigQuery (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect CloudTalk and Google Cloud BigQuery
CloudTalk + Google Cloud BigQuery + Google Sheets: This automation analyzes call data from CloudTalk in Google Cloud BigQuery, calculates key performance indicators (KPIs), and then updates a Google Sheet with the summarized metrics for performance tracking and reporting.
Google Cloud BigQuery + CloudTalk + Slack: When Google Cloud BigQuery detects unusual call volume patterns based on CloudTalk data through a scheduled query, a notification is sent to a designated Slack channel to alert support teams about the anomaly.
CloudTalk and Google Cloud BigQuery integration alternatives
About CloudTalk
Automate CloudTalk call and SMS data within Latenode. Trigger workflows on new calls, messages, or agent status changes. Update CRMs, send alerts, or generate reports automatically. Use Latenode's visual editor and data transformation tools to customize call center automations without complex coding, and scale your workflows efficiently.
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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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See how Latenode works
FAQ CloudTalk and Google Cloud BigQuery
How can I connect my CloudTalk account to Google Cloud BigQuery using Latenode?
To connect your CloudTalk account to Google Cloud BigQuery on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select CloudTalk and click on "Connect".
- Authenticate your CloudTalk and Google Cloud BigQuery accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze call sentiment in BigQuery from CloudTalk?
Yes, you can! Latenode lets you automate data transfer. Analyze sentiment trends and improve customer interactions, all with no-code ease.
What types of tasks can I perform by integrating CloudTalk with Google Cloud BigQuery?
Integrating CloudTalk with Google Cloud BigQuery allows you to perform various tasks, including:
- Backing up CloudTalk call data to Google Cloud BigQuery automatically.
- Analyzing call duration trends and agent performance in BigQuery.
- Creating custom reports on call outcomes and customer satisfaction.
- Tracking the frequency of specific keywords used during calls.
- Aggregating call data with other business metrics in BigQuery.
Can I use JavaScript code to transform CloudTalk data before loading it?
Yes! Latenode supports JavaScript code blocks. You can transform data from CloudTalk before sending it to Google Cloud BigQuery.
Are there any limitations to the CloudTalk and Google Cloud BigQuery integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data loading may take time depending on the data volume.
- Complex data transformations may require advanced JavaScript knowledge.
- Real-time data synchronization depends on CloudTalk’s API capabilities.