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Google BigQuery
Lotame

Integrate your Google BigQuery Data Warehouse with Lotame

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 Lotame and all of your other cloud tools.

Easy Google BigQuery to Lotame 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 Lotame. 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 Lotame and RudderStack

Send real-time data

Send real-time data from multiple sources to Lotame.

Easily send user data

Automatically send user information to Lotame.

Easily flag conversions

Automatically tag existing events as conversions in Lotame.

Frequently Asked Questions

With Rudderstack, integration between Google BigQuery and Lotame is simple. Set up a Google BigQuery source and start sending data.
Pricing Google BigQuery and Lotame can vary based on the way they charge. Check out our pricing page for more info. Or give us a try for FREE.
Timing can vary based on your tech stack and the complexity of your data needs for Google BigQuery and Lotame.

Use the Lotame integration with other popular sources

About Lotame

Lotame is a data enrichment platform used mainly in the marketing, publishing, and digital advertising industries. Its real-time data management solutions help you find new customers, increase engagement, and LTV.

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.