Data observability is the ability to see and understand what data systems are doing in real time, including how data changes, moves, and behaves across pipelines. It focuses on detecting issues such as anomalies, drift, delays, or unexpected changes as early as possible.

Why it matters:
Strong data observability helps organizations catch data drift and abnormal behavior before it causes downstream impact. For AI systems, this early visibility is critical to maintaining reliability, accuracy, and trust.