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

Add the Google Cloud BigQuery Node
Select the Google Cloud BigQuery node from the app selection panel on the right.

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

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Authenticate Google Sheets
Now, click the Google Sheets node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Sheets settings. Authentication allows you to use Google Sheets through Latenode.
Configure the Google Cloud BigQuery and Google Sheets 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 and Google Sheets 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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AI Anthropic Claude 3
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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery, Google Sheets, 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 and Google Sheets integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Google Sheets (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 and Google Sheets
Google Cloud BigQuery + Google Sheets + Slack: Analyze data in BigQuery, update specific cells in a Google Sheet with the results, and then send a message to a Slack channel to notify the team.
Google Sheets + Google AI + Google Cloud BigQuery: When a new row is added to a Google Sheet, send the row's data to Google AI's Gemini model for analysis. The AI's response is then imported into Google BigQuery.
Google Cloud BigQuery and Google Sheets integration alternatives
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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About Google Sheets
Use Google Sheets in Latenode to automate data entry, reporting, and analysis. Read/write data to spreadsheets as part of larger workflows triggered by events or schedules. Avoid manual updates by linking Sheets to other apps. Integrate data from any source via API and transform it into actionable insights.
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See how Latenode works
FAQ Google Cloud BigQuery and Google Sheets
How can I connect my Google Cloud BigQuery account to Google Sheets using Latenode?
To connect your Google Cloud BigQuery account to Google Sheets on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery and click on "Connect".
- Authenticate your Google Cloud BigQuery and Google Sheets accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate report generation using data from BigQuery in Sheets?
Yes, easily! Latenode lets you schedule automated workflows, transforming BigQuery data into insightful Google Sheets reports without manual effort, saving you time.
What types of tasks can I perform by integrating Google Cloud BigQuery with Google Sheets?
Integrating Google Cloud BigQuery with Google Sheets allows you to perform various tasks, including:
- Automating data backups from BigQuery to Google Sheets for redundancy.
- Creating custom dashboards in Google Sheets using real-time BigQuery data.
- Generating scheduled reports on BigQuery data and delivering to stakeholders.
- Enriching BigQuery data with information stored in Google Sheets spreadsheets.
- Triggering actions in other apps based on analysis of BigQuery data in Sheets.
What BigQuery datatypes are supported within Latenode integrations?
Latenode supports standard BigQuery datatypes like INTEGER, FLOAT, STRING, BOOLEAN, and TIMESTAMP, ensuring seamless data transfer and transformations.
Are there any limitations to the Google Cloud BigQuery and Google Sheets integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large datasets may experience processing delays due to Google Sheets API limits.
- Complex data transformations might require custom JavaScript code for optimal performance.
- Real-time data synchronization depends on the frequency of workflow executions.