Machine Learning Observability vs Data Observability

Data observability is the practice of monitoring and troubleshooting data pipelines and infrastructure to ensure accurate, complete, and consistent data. Machine learning observability focuses on monitoring and understanding machine learning models' behavior and performance. Both require continuous monitoring and utilize metrics monitoring and anomaly detection techniques.