From Anomaly Detection to Agentic AI: Engineering Intelligent Data Reliability on Databricks

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Explore how Lokeshkumar Madabathula combines Databricks, real-time anomaly detection, lakehouse architecture, and governed Agentic AI for data reliability.
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Lokeshkumar Madabathula explores how enterprises can move beyond reactive data monitoring by combining real-time anomaly detection, Databricks lakehouse architecture, and governed Agentic AI. His proposed framework uses Auto Loader, Structured Streaming, Delta Lake, Isolation Forest, and statistical thresholds to identify abnormal data behavior. An AI-assisted investigation layer then gathers operational context, develops root-cause hypotheses, assesses potential downstream impact, and recommends remediation, with security controls, audit trails, and human oversight governing consequential actions.