Resource data modeling, forecasting and simulation

A method of modeling and simulating resource data comprising:

• receiving resource data including historical time series data regarding data processing tasks and resources for handling the data processing tasks;
• generating updated short-term aggregated data including short-term aggregated data and newer data aggregated after the short-term aggregated data was generated;
• determining if a prior forecasting model exists for a short-term forecast pertaining to a number of the resources required to complete the data processing tasks in a shorter time period;
• obtaining the short-term forecast by employing the prior forecasting model for analyzing the updated short-term aggregated data if the prior forecasting model exists and if an accuracy of an output of the prior forecasting model for the shorter time period falls within a predetermined accuracy threshold;
• obtaining the short-term forecast by employing a new forecasting model for analyzing the updated short-term aggregated data if the prior forecasting model does not exist or if an accuracy of the output of the prior forecasting model falls outside the predetermined accuracy threshold;
• generating updated long-term aggregated data including the long-term aggregated data and aggregated data generated during a time interval after the long-term aggregated data was generated;
• obtaining the long-term forecast pertaining to a number of the resources required to complete the data processing tasks in a longer time period, wherein the long-term forecast is obtained by analyzing the updated long-term aggregated data employing a long-term forecasting model selected from a plurality of forecasting models;
• and
• generating simulations for one or more parameters associated with the data processing tasks in response to simulation user input based at least on optimized values of one or more of the short-term forecast and the long-term forecast.

A non-transitory processor-readable storage medium comprising machine-readable instructions that cause a processor to:

• receive input regarding one of a short-term forecast and a long-term forecast to be generated, the short-term forecast and the long-term forecast pertaining to a number of data processing tasks expected to be received in a corresponding one of a shorter time period and a longer time period;
• if the input specifies the short-term forecast, then:
• obtain short-term aggregated data by aggregating time series data pertaining to the data processing tasks for the shorter time period;
• generate updated short-term aggregated data including short-term aggregated data and aggregated data obtained from a time interval since the short-term aggregated data was generated and a specified time;
• if an accuracy of an output of a prior short-term forecasting model falls within a predetermined threshold,
• obtain the short-term forecast by employing the prior short-term forecasting model for analyzing the updated short-term aggregated data;
• if an accuracy of the output of the prior short-term forecasting model falls outside the predetermined threshold,
• obtain the short-term forecast by employing a new short-term forecasting model for analyzing the updated short-term aggregated data;
• and
• if the input requires the long-term forecast, then:
• obtain long-term aggregated data by aggregating the time series data for the longer time period;
• generate updated long-term aggregated data including the long-term aggregated data and aggregated data obtained from a time interval since the long-term aggregated data was generated and the specified time;
• select a long-term forecasting model from a plurality of long-term forecasting models based on an accuracy of an output of the selected long-term forecasting model falling within the predetermined threshold;
• obtain the long-term forecast by employing the selected long-term forecasting model for analyzing the updated long-term aggregated data;
• calculate a number of resources required to handle the data processing tasks expected to be received in the corresponding one of the shorter time period and the longer time period;
• and
• generate simulations for one or more parameters associated with the data processing tasks in response to simulation user input based at least on optimized values of one or more of the short-term forecast and the long-term forecast.