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

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Authenticate Moco
Now, click the Moco node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Moco settings. Authentication allows you to use Moco through Latenode.
Configure the Google Cloud BigQuery (REST) and Moco 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 Moco 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), Moco, 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 Moco integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Moco (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 Moco
Moco + Google Cloud BigQuery (REST) + Google Sheets: When new events are logged in Moco, they trigger the insertion of data into a BigQuery table. Subsequently, a query job is executed to analyze the data, and the results are then visualized by updating values in Google Sheets.
Moco + Google Cloud BigQuery (REST) + Slack: As project hours are tracked in Moco, this data is inserted into BigQuery for analysis. When project hours exceed a predefined limit, a query job identifies the overage, and a notification is sent to project managers via Slack.
Google Cloud BigQuery (REST) and Moco 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 Moco
Use Moco in Latenode to track time and expenses. Automate reporting, invoice creation, and project budget monitoring. Connect Moco to accounting or CRM systems for streamlined financial workflows. Build flexible, customized solutions without code, and scale automations as your business grows inside Latenode's visual environment.
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FAQ Google Cloud BigQuery (REST) and Moco
How can I connect my Google Cloud BigQuery (REST) account to Moco using Latenode?
To connect your Google Cloud BigQuery (REST) account to Moco 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 Moco 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) and Moco?
Yes, you can! Latenode's data transformation tools combined with BigQuery's analytics enable efficient cost analysis pulled from Moco, providing insights for better project management.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Moco?
Integrating Google Cloud BigQuery (REST) with Moco allows you to perform various tasks, including:
- Automatically archive Moco data to Google Cloud BigQuery for compliance.
- Build custom dashboards visualizing Moco time tracking data in BigQuery.
- Trigger Moco project updates based on BigQuery analysis results.
- Synchronize Moco customer data with BigQuery datasets.
- Create reports correlating billable hours with project costs.
How secure is my Google Cloud BigQuery (REST) data within Latenode?
Latenode employs encryption and secure authentication protocols, ensuring data privacy and integrity during Google Cloud BigQuery (REST) and Moco integration workflows.
Are there any limitations to the Google Cloud BigQuery (REST) and Moco integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Initial data synchronization may take time for large datasets.
- Complex queries may require advanced Google Cloud BigQuery (REST) knowledge.
- Real-time data updates depend on the polling frequency configured.