Glossary

Outlier detection is the process of identifying data points that significantly deviate from expected patterns within a dataset. These anomalies can signal unusual user behavior, data entry errors, or system glitches—and are critical for maintaining data quality, improving analysis accuracy, and flagging events that could skew key performance metrics or signal important trends.