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

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Authenticate Box
Now, click the Box node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Box settings. Authentication allows you to use Box through Latenode.
Configure the Google Cloud BigQuery (REST) and Box 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 Box 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), Box, 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 Box integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Box (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 Box
Google Cloud BigQuery (REST) + Box + Slack: When a new table is created in BigQuery, a query job is initiated to analyze the data. The results are then stored as a text file in Box, and a summary of the analysis is sent to a Slack channel.
Box + Google Cloud BigQuery (REST) + Google Sheets: When a new file is added to a Box folder, its data is analyzed using BigQuery. Insights from this analysis are then inserted as new rows into a Google Sheet.
Google Cloud BigQuery (REST) and Box 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 Box
Automate Box file management within Latenode workflows. Trigger actions based on file uploads, updates, or deletions. Streamline content workflows: automatically process files, extract data, and route them to other apps like CRMs or databases. Use Latenode’s visual editor to build flexible, scalable solutions without code, and reduce manual file handling.
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See how Latenode works
FAQ Google Cloud BigQuery (REST) and Box
How can I connect my Google Cloud BigQuery (REST) account to Box using Latenode?
To connect your Google Cloud BigQuery (REST) account to Box 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 Box accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I archive BigQuery data in Box automatically?
Yes, you can! Latenode allows you to automate data archiving from Google Cloud BigQuery (REST) to Box. This ensures secure backups and simplifies compliance reporting.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Box?
Integrating Google Cloud BigQuery (REST) with Box allows you to perform various tasks, including:
- Automatically backing up database exports into secure Box folders.
- Creating reports in BigQuery and saving them directly to Box.
- Sharing analyzed sales data from BigQuery via Box with stakeholders.
- Triggering workflows when new datasets are added to BigQuery.
- Managing user permissions on Box based on BigQuery data insights.
How does Latenode handle BigQuery API authentication?
Latenode securely manages Google Cloud BigQuery (REST) authentication using industry-standard protocols, simplifying secure data access and automation.
Are there any limitations to the Google Cloud BigQuery (REST) and Box integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large data transfers from Google Cloud BigQuery (REST) to Box might take time.
- Box storage limits can affect the amount of data you can archive.
- Complex BigQuery queries require optimization for efficient workflow execution.