Data Anomaly Detection
Anomalies often stem from default values, null entries, manual input or rounding mistakes. While many of these anomalies indicate bad data, not all do. However, if any data is found to be incorrect, it’s important to clear these values to prevent skewing your analysis. Our new Anomaly Detection window provides visualization tools to help you investigate any flagged anomalies and take appropriate action.
