Integrate your Google BigQuery Data Warehouse with Google Sheets
Don't go through the pain of direct integration. RudderStack’s Reverse ETL connection makes it easy to send data from your Google BigQuery Data Warehouse to Google Sheets and all of your other cloud tools.
Easy Google BigQuery to Google Sheets integration with RudderStack
RudderStack’s open source Reverse ETL connection allows you to integrate RudderStack with your your Google BigQuery Data Warehouse to track event data and automatically send it to Google Sheets. With the RudderStack Reverse ETL connection, you do not have to worry about having to learn, test, implement or deal with changes in a new API and multiple endpoints every time someone asks for a new integration.
Popular ways to use Google Sheets and RudderStack
Easily populate Google Sheets with event data.
Map event properties to columns in Google Sheets.
Automatically create new rows in Google Sheets with event data.
Frequently Asked Questions
With Rudderstack, integration between Google BigQuery source and Google Sheets is simple. Set up a Google BigQuery source source and start sending data.
Timing can vary based on your tech stack and the complexity of your data needs for Google BigQuery source and Google Sheets.
Yes, RudderStack streamlines the integration and management of your connection between Google BigQuery & Google Sheets, but you check out our guide on How To Send Data From Your Unity App to Google Sheets to learn how to connect the tools manually.
About Google Sheets
Google Sheets is the most popular cloud-based spreadsheet program that lets you create and format your spreadsheets and share them simultaneously with other people. Everyone from businesses and schools uses Google Sheets to manage their day-to-day spreadsheet data. The updated spreadsheets are automatically saved in real-time and are easily accessible from your Google Drive.
About Google BigQuery
Google BigQuery is a fully-managed cloud data warehouse that allows you to store and analyze petabytes of data in no time. It is serverless, highly scalable, and cost-effective and is designed for businesses to analyze massive datasets and make informed business decisions. Google BigQuery also allows running complex analytical SQL-based queries using built-in machine learning capabilities.