Understanding the root causes behind anomalies in time series data is crucial for effective anomaly detection.
Combining detection techniques with methods that explain root causes is key to gaining deeper insights into unusual patterns.
Merely flagging anomalies is insufficient; understanding why they occur is essential for meaningful analysis.
The importance of exploring techniques beyond detection to uncover reasons behind anomalies is highlighted in a personal experience of facing a spike in sales data.