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Scalable Data Management for Kafka and Beyond

Data in motion has changed both the scale and scope of data and analytics - enabling organizations to capture more information and use it more effectively. But to get the most value from it - you need to know what’s there, make it risk aware, and take action on it. In this session, you’ll learn how to leverage modern ML-augmented data management solutions to automatically find, identify, and classify sensitive data across Spark, Databricks, and beyond - and how to apply policies for compliance and risk mitigation to get the most value from our data.

Moderator

Dan Rice