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

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Canny

Authenticate Canny
Now, click the Canny node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Canny settings. Authentication allows you to use Canny through Latenode.
Configure the Google Cloud BigQuery and Canny 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 Canny 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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Canny
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, Canny, 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 Canny integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Canny (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 Canny
Canny + Google Cloud BigQuery + Slack: When a new post is created in Canny, its details are sent to Google Cloud BigQuery for analysis. Trending posts are then identified, and a summary is posted to a designated Slack channel.
Canny + Google Cloud BigQuery + Google Sheets: When a new comment is added in Canny, the details are sent to Google Cloud BigQuery for trend analysis. The analyzed data is then used to update a Google Sheets spreadsheet to visualize user feedback trends.
Google Cloud BigQuery and Canny 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 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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See how Latenode works
FAQ Google Cloud BigQuery and Canny
How can I connect my Google Cloud BigQuery account to Canny using Latenode?
To connect your Google Cloud BigQuery account to Canny 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 Canny accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze Canny feedback data using BigQuery?
Yes, you can! Latenode's flexible data mapping allows seamless transfer, enabling in-depth analysis and custom reports within BigQuery. Get valuable insights to improve product strategy.
What types of tasks can I perform by integrating Google Cloud BigQuery with Canny?
Integrating Google Cloud BigQuery with Canny allows you to perform various tasks, including:
- Automatically exporting new Canny feedback to Google Cloud BigQuery for analysis.
- Updating Canny posts with data insights derived from Google Cloud BigQuery.
- Creating custom dashboards in Google Cloud BigQuery based on Canny feedback.
- Triggering Canny actions based on data changes in Google Cloud BigQuery.
- Enriching Canny data with external sources via Google Cloud BigQuery.
Can I transform data between Google Cloud BigQuery and Canny in Latenode?
Yes, Latenode's data transformation tools allow you to map and modify data, ensuring compatibility between Google Cloud BigQuery and Canny.
Are there any limitations to the Google Cloud BigQuery and Canny integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data synchronization may take time depending on the data volume.
- Complex data transformations may require JavaScript knowledge.
- API rate limits of Google Cloud BigQuery and Canny may impact performance.