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

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

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

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TidyCal

Authenticate TidyCal
Now, click the TidyCal node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your TidyCal settings. Authentication allows you to use TidyCal through Latenode.
Configure the Google Cloud BigQuery and TidyCal 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 and TidyCal 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.

JavaScript
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AI Anthropic Claude 3
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TidyCal
Trigger on Webhook
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Google Cloud BigQuery
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Iterator
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud BigQuery, TidyCal, 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 and TidyCal integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and TidyCal (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 and TidyCal
TidyCal + Google Sheets + Slack: When a new booking is made in TidyCal, the details are added to a Google Sheet. If a specific user's total booked time exceeds a threshold (simulated with a search and update action), a thank you message is sent to them in Slack.
TidyCal + Google BigQuery + Google Sheets: When a new booking is created in TidyCal, the booking data is tracked in Google Sheets. Google BigQuery actions are unavailable therefore, the data is added to Google Sheets to track the scheduled appointments. Weekly trends can be visualized from this data.
Google Cloud BigQuery and TidyCal integration alternatives
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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About TidyCal
TidyCal in Latenode streamlines appointment scheduling. Automate follow-ups, CRM updates, or payment processing after each booking. Use Latenode to connect TidyCal to any app via API, transform booking data with JavaScript, and build custom workflows without code. No per-step cost, full control.
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See how Latenode works
FAQ Google Cloud BigQuery and TidyCal
How can I connect my Google Cloud BigQuery account to TidyCal using Latenode?
To connect your Google Cloud BigQuery account to TidyCal on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery and click on "Connect".
- Authenticate your Google Cloud BigQuery and TidyCal accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze TidyCal bookings in BigQuery?
Yes, you can! Latenode lets you automatically sync TidyCal booking data to Google Cloud BigQuery for advanced analysis. Benefit from enhanced insights and data-driven decisions using BigQuery's power.
What types of tasks can I perform by integrating Google Cloud BigQuery with TidyCal?
Integrating Google Cloud BigQuery with TidyCal allows you to perform various tasks, including:
- Analyze booking trends and identify peak scheduling times.
- Automatically update BigQuery datasets with new booking information.
- Create custom reports combining booking data with other business metrics.
- Trigger personalized email campaigns based on booking patterns.
- Visualize booking data using connected BI tools like Tableau.
How secure is my Google Cloud BigQuery data within Latenode?
Latenode uses industry-standard security protocols to encrypt and protect your data during transfer and storage, ensuring confidentiality and integrity.
Are there any limitations to the Google Cloud BigQuery and TidyCal integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data synchronization might take time depending on the dataset size.
- Complex queries in Google Cloud BigQuery might require advanced skills.
- Real-time data updates depend on the TidyCal API availability.