How to connect Microsoft Excel and Google Cloud BigQuery
Create a New Scenario to Connect Microsoft Excel and Google Cloud BigQuery
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 Microsoft Excel, triggered by another scenario, or executed manually (for testing purposes). In most cases, Microsoft Excel or Google Cloud BigQuery will be your first step. To do this, click "Choose an app," find Microsoft Excel or Google Cloud BigQuery, and select the appropriate trigger to start the scenario.

Add the Microsoft Excel Node
Select the Microsoft Excel node from the app selection panel on the right.


Microsoft Excel

Configure the Microsoft Excel
Click on the Microsoft Excel node to configure it. You can modify the Microsoft Excel URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Cloud BigQuery Node
Next, click the plus (+) icon on the Microsoft Excel node, select Google Cloud BigQuery from the list of available apps, and choose the action you need from the list of nodes within Google Cloud BigQuery.


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Authenticate Google Cloud BigQuery
Now, click the Google Cloud BigQuery node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud BigQuery settings. Authentication allows you to use Google Cloud BigQuery through Latenode.
Configure the Microsoft Excel and Google Cloud BigQuery 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 Microsoft Excel and Google Cloud BigQuery 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 Microsoft Excel, Google Cloud BigQuery, 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 Microsoft Excel and Google Cloud BigQuery integration works as expected. Depending on your setup, data should flow between Microsoft Excel and Google Cloud BigQuery (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Microsoft Excel and Google Cloud BigQuery
Microsoft Excel + Google Sheets: When a new row is added to an Excel worksheet, the data is extracted and added as a new row in a specified Google Sheet for centralized data collection and analysis.
Microsoft Excel + Google Sheets: When a new row is added to an Excel table, the data is extracted and used to update an existing row in Google Sheets based on a search in a specific column.
Microsoft Excel and Google Cloud BigQuery integration alternatives

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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About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
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FAQ Microsoft Excel and Google Cloud BigQuery
How can I connect my Microsoft Excel account to Google Cloud BigQuery using Latenode?
To connect your Microsoft Excel account to Google Cloud BigQuery on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Microsoft Excel and click on "Connect".
- Authenticate your Microsoft Excel and Google Cloud BigQuery accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate data transfers between Excel and BigQuery?
Yes, you can! Latenode simplifies automating data transfers. Schedule regular uploads from Excel to BigQuery, ensuring your data warehouse is always up-to-date with zero manual work.
What types of tasks can I perform by integrating Microsoft Excel with Google Cloud BigQuery?
Integrating Microsoft Excel with Google Cloud BigQuery allows you to perform various tasks, including:
- Automatically backing up Excel data to Google Cloud BigQuery for secure storage.
- Scheduling regular data imports from Google Cloud BigQuery into Excel spreadsheets.
- Creating custom reports in Excel using data pulled directly from BigQuery.
- Validating Excel data against large datasets stored in Google Cloud BigQuery.
- Triggering data analysis in BigQuery when new data is added to Excel.
HowdoIhandlelargeExceldatainLatenodeforBigQueryintegrations?
Latenode efficiently handles large Excel files using streams, parsing data in chunks. This prevents memory issues and allows seamless BigQuery uploads.
Are there any limitations to the Microsoft Excel and Google Cloud BigQuery integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Very large Excel files might require optimized workflows for efficient processing.
- Complex Excel formulas might not directly translate to Google Cloud BigQuery functions.
- Real-time, two-way synchronization is not supported; updates are batch-processed.