How to connect Google Cloud BigQuery (REST) and Qwilr
Create a New Scenario to Connect Google Cloud BigQuery (REST) and Qwilr
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 Qwilr will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery (REST) or Qwilr, 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.

Google Cloud BigQuery (REST)
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 Qwilr Node
Next, click the plus (+) icon on the Google Cloud BigQuery (REST) node, select Qwilr from the list of available apps, and choose the action you need from the list of nodes within Qwilr.

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Authenticate Qwilr
Now, click the Qwilr node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Qwilr settings. Authentication allows you to use Qwilr through Latenode.
Configure the Google Cloud BigQuery (REST) and Qwilr 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 Qwilr 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), Qwilr, 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 Qwilr integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Qwilr (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 Qwilr
Qwilr + Google Cloud BigQuery (REST) + Slack: When a Qwilr page is accepted, query Google Cloud BigQuery for related data, and then send a message to a Slack channel to alert the sales team.
Qwilr + Pipedrive + Google Cloud BigQuery (REST): When a Qwilr page is accepted, create a deal in Pipedrive and log deal creation in Google Cloud BigQuery for data analysis.
Google Cloud BigQuery (REST) and Qwilr 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 Qwilr
Automate Qwilr quote creation inside Latenode workflows. Automatically generate Qwilr proposals when triggered by new CRM leads or form submissions. Send data to Qwilr, then use Latenode to track views, trigger follow-ups, and update your database—no manual data entry needed. Scale personalized sales flows with ease.
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FAQ Google Cloud BigQuery (REST) and Qwilr
How can I connect my Google Cloud BigQuery (REST) account to Qwilr using Latenode?
To connect your Google Cloud BigQuery (REST) account to Qwilr 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 Qwilr accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically update Qwilr quotes from BigQuery data?
Yes, you can. Latenode lets you automate data updates, ensuring your Qwilr quotes always reflect the latest BigQuery insights, saving time and improving accuracy.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Qwilr?
Integrating Google Cloud BigQuery (REST) with Qwilr allows you to perform various tasks, including:
- Automatically generating Qwilr proposals from BigQuery sales data.
- Updating client information in Qwilr based on BigQuery data analysis.
- Creating personalized Qwilr reports using BigQuery customer insights.
- Triggering Qwilr project creation when new data is added to BigQuery.
- Monitoring proposal performance in BigQuery, updating Qwilr status accordingly.
CanIuseJavaScripttransformBigQuerydatatopreparetforQwilr?
Yes, Latenode allows JavaScript code blocks to transform data. This enables seamless data preparation for use in Qwilr workflows and templates.
Are there any limitations to the Google Cloud BigQuery (REST) and Qwilr integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations might require advanced JavaScript coding skills.
- Large datasets in BigQuery could impact workflow execution speed.
- API rate limits for both Google Cloud BigQuery (REST) and Qwilr apply.