Patent ID: 8140454

Claim:
A method of analyzing data in a business processing management environment, the method comprising: identifying a plurality of performance indicators, each said performance indicator being related to a process and/or system component; defining at least one rule to monitor at least one said performance indicator of a process and/or system component; creating a prediction template to identify at least one rule on which to create a prediction, the prediction template including a past interval indicative of an amount of data to be analyzed before making the prediction, a future interval indicative of how far into the future the prediction is to be made, and an accuracy threshold indicative of a probability level to be reached in making the prediction; gathering data for each said performance indicator over a plurality of collection intervals; gardening the gathered data to discard gathered data within a normal operating range for a given collection interval; applying a time-series transform to the gardened data to normalize any variations in collection intervals; feeding the transformed gardened data into a dynamically updatable Naïve Bayesian Network (NBN) such that an entry is created for the transformed gardened data when the NBN does not include an entry for the transformed gardened data, and such that an already existing entry for the transformed gardened data is updated when the NBN includes an entry corresponding to the transformed gardened data; making the prediction and determining an accuracy thereof using probabilities computed by the NBN; and updating a relevance value associated with each performance indicator in a rule using the gardened data for root cause analysis, wherein the gathering and the making of the prediction are performed substantially in real-time.