Mass anomaly detection refers to identifying unusual patterns or rare events in large datasets, which may indicate critical events such as fraud, system failures, or previously undetected data patterns. Utilizing advanced algorithms and statistical techniques, it enhances predictive maintenance and risk management by detecting outliers that deviate significantly from established norms.