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

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


Canny

Add the Google Cloud BigQuery (REST) Node
Next, click the plus (+) icon on the Canny 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 Canny 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 Canny 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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Save and Activate the Scenario
After configuring Canny, 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 Canny and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Canny 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 Canny and Google Cloud BigQuery (REST)
Canny + Google Cloud BigQuery (REST) + Slack: When a new feature request is submitted in Canny, the data is inserted into a Google Cloud BigQuery dataset for analysis. A summary of the new request is then sent to a designated Slack channel.
Canny + Google Sheets + Slack: When a post's status is changed in Canny, the update is logged in a Google Sheets spreadsheet. A Slack notification is sent to a channel to inform the team of the status change.
Canny and Google Cloud BigQuery (REST) integration alternatives

About Canny
Integrate Canny with Latenode to automate feedback management. Capture user suggestions and bug reports directly, then route them to the right teams. Use AI to categorize input, update task trackers, and notify users of progress, automating the feedback loop and improving responsiveness.
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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 Canny and Google Cloud BigQuery (REST)
How can I connect my Canny account to Google Cloud BigQuery (REST) using Latenode?
To connect your Canny account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Canny and click on "Connect".
- Authenticate your Canny and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze Canny feedback trends in BigQuery?
Yes, you can! Latenode automates data transfer, letting you analyze Canny feedback trends in BigQuery. This provides deeper insights to inform product decisions.
What types of tasks can I perform by integrating Canny with Google Cloud BigQuery (REST)?
Integrating Canny with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Automatically back up Canny feedback data to BigQuery for archival purposes.
- Analyze user feedback from Canny alongside other business metrics in BigQuery.
- Create custom dashboards in BigQuery visualizing Canny feature request trends.
- Trigger alerts based on sentiment analysis of Canny feedback stored in BigQuery.
- Enrich Canny data in BigQuery with data from other sources for comprehensive reporting.
How do I ensure Canny data is accurately mapped to BigQuery fields?
Latenode’s visual editor allows precise field mapping and data transformations, guaranteeing data accuracy between Canny and BigQuery.
Are there any limitations to the Canny and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by the Canny API may affect data synchronization frequency.
- Initial data migration from Canny to BigQuery may require significant processing time.
- Complex data transformations might require JavaScript coding within Latenode.