1. A machine-implemented method comprising: automatically identifying a finite set of detected anomalies within an anomalies distribution space having one or more feature-representing dimensional axes; automatically aggregating together two or more of the detected anomalies for forming a corresponding anomalies reporting alert corresponding to the aggregated two or more of the detected anomalies; before aggregating together said two or more of the detected anomalies, automatically identifying by way of a computationally less intensive variance analysis, outlier anomalies within the finite set that are least clustered together with others of the anomalies in the finite set; not performing aggregation on the identified outlier anomalies; and automatically forming corresponding anomaly reporting alerts for respective ones of the identified outlier anomalies.