How to connect Google Cloud BigQuery and Sendy
Create a New Scenario to Connect Google Cloud BigQuery and Sendy
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 Sendy will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Sendy, 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 Sendy Node
Next, click the plus (+) icon on the Google Cloud BigQuery node, select Sendy from the list of available apps, and choose the action you need from the list of nodes within Sendy.

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Authenticate Sendy
Now, click the Sendy node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Sendy settings. Authentication allows you to use Sendy through Latenode.
Configure the Google Cloud BigQuery and Sendy 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 Sendy 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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Sendy
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, Sendy, 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 Sendy integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Sendy (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 Sendy
Google Cloud BigQuery + Sendy + Google Sheets: Analyze email campaign data from BigQuery (using external tools), update subscriber lists in Sendy based on the analysis, and summarize the changes in Google Sheets.
Sendy + Google Cloud BigQuery + Slack: Track email campaign performance in Sendy by retrieving subscriber count. Log the data to BigQuery (using external tools). Send alerts to Slack for significant changes in subscriber count based on a threshold.
Google Cloud BigQuery and Sendy 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 Sendy
Use Sendy in Latenode to automate email campaigns without complex coding. Trigger campaigns based on events in other apps (CRM, e-commerce). Latenode lets you process data, filter recipients, and personalize emails with JavaScript or AI nodes before sending via Sendy. Scale outreach efficiently and track results within your workflows.
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See how Latenode works
FAQ Google Cloud BigQuery and Sendy
How can I connect my Google Cloud BigQuery account to Sendy using Latenode?
To connect your Google Cloud BigQuery account to Sendy 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 Sendy accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate email list updates based on BigQuery data?
Yes, with Latenode you can automate email list updates in Sendy based on Google Cloud BigQuery data. Leverage no-code blocks and custom JavaScript for advanced data manipulation and segmentation.
What types of tasks can I perform by integrating Google Cloud BigQuery with Sendy?
Integrating Google Cloud BigQuery with Sendy allows you to perform various tasks, including:
- Automatically add new leads from BigQuery to a Sendy mailing list.
- Update subscriber details in Sendy based on BigQuery customer data.
- Trigger targeted email campaigns based on BigQuery analysis results.
- Segment Sendy subscribers using data insights from Google Cloud BigQuery.
- Track email campaign performance metrics in Google Cloud BigQuery for analysis.
How do I handle large datasets from Google Cloud BigQuery efficiently?
Latenode's architecture allows you to process large datasets from Google Cloud BigQuery by implementing optimized data streaming and transformation techniques.
Are there any limitations to the Google Cloud BigQuery and Sendy integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data schema setup requires familiarity with Google Cloud BigQuery.
- Complex data transformations might require JavaScript knowledge.
- Rate limits of the Google Cloud BigQuery and Sendy APIs apply.