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

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Authenticate Awork
Now, click the Awork node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Awork settings. Authentication allows you to use Awork through Latenode.
Configure the Google Cloud BigQuery (REST) and Awork 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 Awork 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery (REST), Awork, 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 Awork integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Awork (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 Awork
Google Cloud BigQuery + Awork + Slack: When a specific condition is met in Google Cloud BigQuery (simulated by a new row in Google Sheets), a task is created in Awork, and the project manager is notified via a Slack message.
Awork + Google Cloud BigQuery + Google Sheets: When a new time entry is created in Awork, the data is added to Google Cloud BigQuery (simulated by adding a row to a Google Sheet), which is then used to update billing hour summaries in Google Sheets.
Google Cloud BigQuery (REST) and Awork 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 Awork
Manage Awork tasks in Latenode to automate project updates and reporting. Trigger flows on new tasks, sync deadlines across tools, or create custom reports. Use Latenode's logic functions and webhooks to connect Awork to any system, crafting automated workflows without complex coding, and scale project management tasks efficiently.
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FAQ Google Cloud BigQuery (REST) and Awork
How can I connect my Google Cloud BigQuery (REST) account to Awork using Latenode?
To connect your Google Cloud BigQuery (REST) account to Awork 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 Awork accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze project profitability using Google Cloud BigQuery (REST) data in Awork?
Yes, you can! Latenode's data transformation tools allow you to reshape BigQuery data for reporting in Awork. Gain clearer insights on project costs & ROI.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Awork?
Integrating Google Cloud BigQuery (REST) with Awork allows you to perform various tasks, including:
- Automatically update Awork tasks based on data analysis in BigQuery.
- Create custom reports in Awork using BigQuery datasets.
- Trigger Awork project updates based on BigQuery data thresholds.
- Synchronize project budgets between BigQuery and Awork.
- Visualize BigQuery data related to project performance within Awork.
HowdoIsecurelystoremyGoogleCloudBigQuery(REST)credentials?
Latenode uses encrypted storage for all credentials, ensuring your Google Cloud BigQuery (REST) and Awork data remains secure during automation.
Are there any limitations to the Google Cloud BigQuery (REST) and Awork integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data synchronization can take time depending on dataset size.
- Complex data transformations may require JavaScript knowledge.
- API rate limits of both Google Cloud BigQuery (REST) and Awork apply.