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Easy Google BigQuery to Madkudu 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 Madkudu. 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 Madkudu
Create leads automatically
Automatically create customer records in real time in Madkudu when someone signs up.
Enable your marketing team to trigger email, SMS, mobile, and personalization campaigns based on user actions.
Easily update user traits
Provide your marketing team with advanced segmentation capabilities by updating user traits in real time.
Frequently Asked Questions
How do you integrate your Google BigQuery data warehouse with Madkudu?
With Rudderstack, integration between Google BigQuery source and Madkudu is simple. Set up a Google BigQuery source source and start sending data.
Is it expensive to integrate Google BigQuery source with Madkudu?
How long does it take to integrate Google BigQuery source with Madkudu?
Timing can vary based on your tech stack and the complexity of your data needs for Google BigQuery source and Madkudu.
RudderStack Google BigQuery Documentation
Refer to our step-by-step guide and start using Google BigQuery today
Madkudu is a predictive lead scoring solution that helps B2B market leaders to accelerate growth using their customer data. It applies machine learning algorithms to customer data to score leads based on past activity or attributes.
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.