Description
Sudden spikes, invalid ranges, or duplicate entries may indicate data corruption or external issues. Use anomaly detection techniques or rules (e.g., z-scores, min/max range filters) to flag and investigate outliers in datasets.
Outlier and Anomaly Detection
₦71,710.97
Flags unexpected or suspicious data values.
Zubairu –
Before using their solution, our reports were often skewed by unnoticed data outliers. Now, with accurate detection and filtering in place, our analytics are more reliable and decision-making has improved.
Udeme –
The outlier detection tools they implemented gave us real-time visibility into system behavior. We now catch performance dips and data anomalies instantly, improving response time and system uptime.
Hawawu –
Their anomaly detection system flagged irregular patterns in our transaction data that we would’ve missed entirely. It helped us prevent potential fraud and improve operational oversight.