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Time Series Anomaly Detection and Root Cause Analysis: Complete Guide to Causal Methods

  • 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.

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