Handling Data Anomalies

Overview:

Detect and manage outliers or anomalies in customer service center (CSC) data to ensure data accuracy and reliability.

Transformations:

1. Outlier Detection:

   • Identify anomalies in ticket resolution patterns, including unusually high service durations, unexpected spikes in customer complaints, or irregular ticket volumes.
   • Learn more about Outlier Detection

2. Anomaly Flagging:

   • Apply anomaly detection techniques to flag tickets with outlier response times or resolution times for further investigation.
   • Learn more about Anomaly Flagging

3. Data Smoothing:

   • Use rolling averages or other smoothing techniques to adjust for seasonal ticket volume spikes and extract meaningful trends without distortion from rare events.
   • Learn more about Data Smoothing