Build an AI Personalization Engine with Confluent & Databricks

This post introduces a quickstart for building an AI-powered marketing personalization engine by integrating Confluent Cloud and Databricks. It details the architecture and data flow, highlighting the use of Confluent's Oracle XStream CDC Source Connector for ingesting operational data, Apache Flink for stream processing and AI model inference, and Tableflow for seamless synchronization of Kafka data as Delta Lake tables in Databricks. The quickstart guides users through setting up the environment, deploying cloud infrastructure, ingesting mock data, processing and enriching data with Flink, streaming data products to Delta Lake with Tableflow, and generating insights and campaigns with Databricks.