A user-friendly tool to detect anomalies in time series data without explicitly defining normal and abnormal criteria. The solution is able to uncover hidden temporal patterns such as trends and seasonal fluctuations (periodic patterns) and identify observations that do not conform to the expected behavior pattern. The solution is also able to adjust its knowledge by collecting user feedbacks to provide more accurate predictions.