Anomaly Detection

Anomaly detection is the process of identifying data points, events or patterns that deviate significantly from the norm or expected behavior. Also known as outlier detection, it is used to uncover unusual occurrences that may indicate critical incidents such as fraud, system failures, cybersecurity threats or operational issues. Anomaly detection can be applied using statistical methods, machine learning algorithms, or deep learning techniques across time series, spatial, or transactional data. It is widely used in industries like finance, healthcare, manufacturing, and information technology to enhance monitoring, ensure reliability, and trigger timely interventions.