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How to connect Google Cloud BigQuery (REST) and Sendy
Create a New Scenario to Connect Google Cloud BigQuery (REST) 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 (REST), triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery (REST) or Sendy will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Sendy, and select the appropriate trigger to start the scenario.
Add the Google Cloud BigQuery (REST) Node
Select the Google Cloud BigQuery (REST) node from the app selection panel on the right.
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Configure the Google Cloud BigQuery (REST)
Click on the Google Cloud BigQuery (REST) node to configure it. You can modify the Google Cloud BigQuery (REST) 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 (REST) 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 (REST) 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 (REST) 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.
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Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), 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 (REST) and Sendy integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) 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 (REST) and Sendy
Sendy + Google Cloud BigQuery (REST) + Google Sheets: Analyze Sendy email campaign performance data. When a new campaign is created in Sendy, its data is pushed to Google Cloud BigQuery. Then, retrieve the data from BigQuery and visualize key metrics in a Google Sheet for performance tracking and reporting.
Sendy + Google Cloud BigQuery (REST) + Slack: Track Sendy campaign metrics, push significant changes in click-through rates to BigQuery, and alert the marketing team in Slack. When a Sendy campaign is created, key metrics are stored in BigQuery. If the click-through rate significantly changes, a notification is sent to a Slack channel.
Google Cloud BigQuery (REST) and Sendy integration alternatives
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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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
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FAQ Google Cloud BigQuery (REST) and Sendy
How can I connect my Google Cloud BigQuery (REST) account to Sendy using Latenode?
To connect your Google Cloud BigQuery (REST) account to Sendy on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery (REST) and click on "Connect".
- Authenticate your Google Cloud BigQuery (REST) and Sendy accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate email list updates from BigQuery data?
Yes, you can! Latenode enables automated synchronization. Easily update Sendy subscriber lists based on data changes in Google Cloud BigQuery (REST), saving time and improving targeting.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Sendy?
Integrating Google Cloud BigQuery (REST) with Sendy allows you to perform various tasks, including:
- Automatically adding new BigQuery leads to Sendy email lists.
- Segmenting Sendy subscribers based on BigQuery data analysis.
- Triggering Sendy email campaigns from BigQuery data changes.
- Updating custom fields in Sendy with data from BigQuery.
- Removing unsubscribed emails from BigQuery data sets.
HowdoesLatenodehandleBigQuerydata volume forSendyupdates?
Latenode efficiently processes large datasets from Google Cloud BigQuery (REST), ensuring smooth data transfer to Sendy without performance bottlenecks, using optimized batch processing.
Are there any limitations to the Google Cloud BigQuery (REST) 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 both platforms.
- Complex data transformations might need custom JavaScript code.
- Rate limits of both Google Cloud BigQuery (REST) and Sendy apply.
