System and method for automatically identifying an anomalous pattern

A method for automatically identifying an anomalous pattern, the method comprising:

• receiving, at an input unit [102], a stream of data;
• determining, by a processing unit [104], a monitoring metric for at least one of one or more dimensions and one or more groups of dimensions associated with the stream of data, at a target time;
• determining, by the processing unit [104], the monitoring metric for at least one of the one or more dimensions and the one or more groups of dimensions, at a benchmark time period;
• identifying, by an identification unit [106], the monitoring metric for at least one of the one or more dimensions and the one or more groups of dimensions at the target time as an outlier to the monitoring metric for at least one of the one or more dimensions and the one or more groups of dimensions at the benchmark time period based at least on an event where the monitoring metric for at least one of the one or more dimensions and the one or more groups of dimensions at the target time is greater than the monitoring metric for at least one of the one or more dimensions and the one or more groups of dimensions at the benchmark time period at least by a threshold value;
• and
• automatically identifying, by the identification unit [106], the anomalous pattern based at least on the identification of the monitoring metric for at least one of the one or more dimensions and the one or more groups of dimensions at the target time as the outlier to the monitoring metric for at least one of the one or more dimensions and the one or more groups of dimensions at the benchmark time period.