Abstract: Systems and method embodying the invention classify portions of a data stream that is received from a production environment. Portions of the data stream are compared to a plurality of templates to determine if the portions of the data appear to match a known template. If there is a match, the data is further analyzed in an attempt to classify the data as being of a one of a plurality of different types that correspond to the matched template.

Abstract: Systems and methods for selecting a forecast model for analyzing time series data operate by identifying a characteristic of a set of time series data, then running tests on the time series data using multiple different forecast models. The forecast model that returns the fewest errors predicting future values of the time series data is selected for use for in analyzing time series data having the identified characteristic. This process is repeated for other sets of time series data having alternate characteristics to identify the forecast models that most accurately predict future values of time series data having those alternate characteristics. Thereafter, it is only necessary to identify the characteristics of a new set of time series data, and then use the forecast model that was selected for time series data having the identified characteristic in order to generate accurate predictions of future values for the new set of time series data.