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

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


Calendly

Configure the Calendly
Click on the Calendly node to configure it. You can modify the Calendly 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 Calendly 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 Calendly 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 Calendly 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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Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Calendly, 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 Calendly and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Calendly 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 Calendly and Google Cloud BigQuery (REST)
Calendly + Google Cloud BigQuery (REST) + Google Sheets: When a new Calendly invitee is created, the information is inserted into a BigQuery table. A daily summary of the meeting data is then extracted from BigQuery and added to a Google Sheet for reporting purposes.
Google Cloud BigQuery (REST) + Calendly + Slack: BigQuery monitors meeting bookings data. When the number of bookings from Calendly falls below a defined threshold (determined by running a query), a notification is sent to a Slack channel to alert the sales team.
Calendly and Google Cloud BigQuery (REST) integration alternatives

About Calendly
Automate meeting scheduling with Calendly in Latenode. Trigger workflows based on new bookings or cancellations. Automatically update CRMs, send personalized follow-ups, or manage team calendars, freeing up valuable time. Latenode adds flexible logic and integrations Calendly lacks, all visually and affordably.
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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 Calendly and Google Cloud BigQuery (REST)
How can I connect my Calendly account to Google Cloud BigQuery (REST) using Latenode?
To connect your Calendly account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Calendly and click on "Connect".
- Authenticate your Calendly and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze event scheduling trends?
Yes, with Latenode! Automatically send Calendly data to Google Cloud BigQuery (REST) for in-depth analysis, uncovering booking patterns and optimizing scheduling efficiency.
What types of tasks can I perform by integrating Calendly with Google Cloud BigQuery (REST)?
Integrating Calendly with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automatically back up Calendly event data to Google Cloud BigQuery (REST).
- Create custom reports on meeting types and attendee demographics.
- Track conversion rates from Calendly bookings to sales outcomes.
- Visualize scheduling data to identify peak demand periods.
- Trigger personalized follow-up sequences based on event data analysis.
How can I filter Calendly events before sending to BigQuery?
Latenode lets you use logic blocks or JavaScript code to filter events, ensuring only relevant data reaches your BigQuery datasets.
Are there any limitations to the Calendly and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data loading from Calendly might require handling rate limits.
- Complex data transformations may necessitate JavaScript code.
- Reporting is limited to the capabilities of Google Cloud BigQuery (REST).