Lindemann (data analytics)

Lindemann in data analytics generally refers to the Lindemann criterion, a concept used to identify failure or significant change in a system based on deviations from expected behavior. It involves monitoring data points to detect when they surpass a certain threshold of difference from the norm, indicating a potential problem or transition. This method helps in early detection of anomalies, faults, or important shifts in data patterns, allowing timely interventions and informed decision-making. In essence, Lindemann provides a quantitative way to recognize when a process or system is deviating from its usual performance.