What is Anomaly Detection?

Anomaly detection is the process of identifying patterns in data that deviate significantly from the norm. It leverages machine learning and statistical techniques to detect unusual behavior, making it essential for applications such as fraud detection, cybersecurity, manufacturing quality control, and healthcare analytics. The two primary approaches to anomaly detection are supervised learning (using labeled data) and unsupervised learning (detecting anomalies without predefined labels). AI-powered anomaly detection is particularly effective for processing large-scale, real-time data, ensuring data integrity, security, and operational efficiency.