Anomaly reduction

Anomaly reduction involves identifying and minimizing unusual or unexpected data points that don't fit normal patterns. These anomalies can result from errors, rare events, or unusual behaviors. By reducing anomalies, organizations can improve the accuracy of their data analysis, decision-making, and system performance. Techniques include cleaning data, applying statistical methods, or using algorithms to detect and handle outliers. The goal is to ensure the analysis reflects typical behavior, leading to more reliable insights and better outcomes.