A method for associating time series data to template time series data patterns to detect current or predict future events, the method comprising: receiving at a processor a data stream transmitted from a sensor configured to measure an operating parameter of a component being monitored, wherein the data stream comprises at least time series data; analyzing the data stream to identify a sequence of interest in the time series data having predictive values by matching patterns in the time series data to a template pattern of a known event; extracting the identified sequence of interest from the time series data; marking the identified sequence of interest as an extracted event; storing the extracted event in a database to indicate a possible detection or prediction of an occurrence of an event; specifying a relationship between the time series data of the extracted event and the template pattern of the known event in quantifiable terms; and quantifying the relationship between the time series data of the extracted event and the known event by calculating a confidence level to denote a statistical probability of occurrence of the event by comparing data patterns of the extracted event with data of the template pattern associated with the known event; wherein the confidence level is a numeric value within a predetermined numeric range of numeric values, wherein one of the numeric values represents a perfect match between the time series data of the extracted event and the template pattern of the known event; acquiring metadata from content of the time series data of the extracted event, wherein the metadata contains information explaining details of the content of the time series data related to the extracted event; and storing in the database the metadata associated with the extracted event. receiving at a processor a data stream transmitted from a sensor configured to measure an operating parameter of a component being monitored, wherein the data stream comprises at least time series data; analyzing the data stream to identify a sequence of interest in the time series data having predictive values by matching patterns in the time series data to a template pattern of a known event; extracting the identified sequence of interest from the time series data; marking the identified sequence of interest as an extracted event; storing the extracted event in a database to indicate a possible detection or prediction of an occurrence of an event; specifying a relationship between the time series data of the extracted event and the template pattern of the known event in quantifiable terms; and quantifying the relationship between the time series data of the extracted event and the known event by calculating a confidence level to denote a statistical probability of occurrence of the event by comparing data patterns of the extracted event with data of the template pattern associated with the known event; wherein the confidence level is a numeric value within a predetermined numeric range of numeric values, wherein one of the numeric values represents a perfect match between the time series data of the extracted event and the template pattern of the known event; acquiring metadata from content of the time series data of the extracted event, wherein the metadata contains information explaining details of the content of the time series data related to the extracted event; and storing in the database the metadata associated with the extracted event.