From Data to Decisions: Real-Time Analytics and ML with Kafka and Databricks

Scalable architecture that integrates a self-managed Kafka environment for event-driven data ingestion with Databricks for structured streaming and analytics. In this paper, we describe a solution that enables real-time anomaly detection and predictive insights, enhancing monitoring capabilities across diverse domains and systems, while ensuring high efficiency, scalability, and versatility in data processing.