Feeling stuck with Segment? Say 👋 to RudderStack.
Easy Google BigQuery to Comscore integration with RudderStack
RudderStack’s open source Reverse ETL connection allows you to integrate RudderStack with your Google BigQuery Data Warehouse to track event data and automatically send it to Comscore. 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 Comscore
Enable real-time data
Automatically send real-time data to marketing analytics, product analytics and business analytics tools.
Track the entire user journey across platforms without the technical headache.
Hot-swap analytics tools
Send existing data feeds to new analytics tools with a few clicks.
Frequently Asked Questions
How do you integrate your Google BigQuery data warehouse with Comscore?
With Rudderstack, integration between Google BigQuery source and Comscore is simple. Set up a Google BigQuery source source and start sending data.
Is it expensive to integrate Google BigQuery source with Comscore?
How long does it take to integrate Google BigQuery source with Comscore?
Timing can vary based on your tech stack and the complexity of your data needs for Google BigQuery source and Comscore.
RudderStack Google BigQuery Documentation
Refer to our step-by-step guide and start using Google BigQuery today
Comscore is a cross-platform media analytics tool that helps you capture vast audience insights across digital, linear TV, over-the-top (OTT), and theatrical viewership. Comscore helps media agencies, brands, and advertisers to combine their consumer data in different ways and ensure that advertising reaches the right audience. Along with the reliable measurement of cross-platform audiences, Comscore aims to provide advertisers with strategies to reach consumers based on more granular data.
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.