What is an anomaly detection system?

An anomaly detection system is designed to identify unusual patterns or outliers in data that deviate from the expected behavior. This is crucial in various domains, such as fraud detection in financial transactions, network security breaches, and equipment malfunction in industrial systems. By recognizing these anomalies, organizations can take preventive measures or investigate further to mitigate potential risks.

Anomaly detection relies on statistical methods, machine learning algorithms, or a combination of both to sift through large datasets and highlight points that do not fit established patterns. This feature is vital for real-time monitoring systems where early detection can significantly improve the response to irregular occurrences.

In contrast, some other options mention functions like identifying common patterns, merging data, or visualizing trends, which are essential data processing and analytics tasks but do not focus on identifying the outlier behavior that an anomaly detection system specifically targets.