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

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Authenticate Microsoft Excel
Now, click the Microsoft Excel node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Microsoft Excel settings. Authentication allows you to use Microsoft Excel through Latenode.
Configure the Google Cloud BigQuery (REST) and Microsoft Excel 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 Microsoft Excel 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), Microsoft Excel, 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 Microsoft Excel integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery (REST) and Microsoft Excel (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 Microsoft Excel
Google Cloud BigQuery (REST) + Microsoft Excel + Slack: When a new table is added to BigQuery, a query job is created, and the results are used to create a report in a new Excel worksheet. A message is then sent to a Slack channel to notify the team about the new report.
Microsoft Excel + Google Cloud BigQuery (REST) + Google Sheets: When a new row is added to an Excel table, the data from the row is inserted into a BigQuery table. Then, a query job is run to analyze this data, and the results are visualized in a Google Sheet.
Google Cloud BigQuery (REST) and Microsoft Excel 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 Microsoft Excel
Automate Excel tasks within Latenode workflows. Read, update, or create spreadsheets directly. Use Excel data to trigger actions in other apps, generate reports, or update databases. No manual data entry; improve accuracy and save time by connecting Excel to other systems via Latenode's visual interface.
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FAQ Google Cloud BigQuery (REST) and Microsoft Excel
How can I connect my Google Cloud BigQuery (REST) account to Microsoft Excel using Latenode?
To connect your Google Cloud BigQuery (REST) account to Microsoft Excel 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 Microsoft Excel accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate monthly report generation using BigQuery data in Excel?
Yes, you can! Latenode automates data transfers, allowing you to pull BigQuery data into Excel and generate reports without manual work. Save time and ensure accuracy effortlessly.
What types of tasks can I perform by integrating Google Cloud BigQuery (REST) with Microsoft Excel?
Integrating Google Cloud BigQuery (REST) with Microsoft Excel allows you to perform various tasks, including:
- Automating the transfer of large datasets from BigQuery to Excel spreadsheets.
- Creating real-time dashboards in Excel using BigQuery data.
- Scheduling regular data exports from BigQuery to update Excel reports.
- Performing custom data analysis in Excel with up-to-date BigQuery information.
- Generating personalized reports by merging BigQuery data with Excel templates.
How secure is my BigQuery data when used within Latenode workflows?
Latenode uses secure authentication methods and encryption to protect your data during BigQuery and Excel integration workflows, ensuring data integrity.
Are there any limitations to the Google Cloud BigQuery (REST) and Microsoft Excel integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large datasets might require optimization for efficient transfer speeds.
- Excel's row limit may restrict the amount of data imported.
- Complex data transformations might necessitate custom JavaScript code.