1. A machine-implemented method to forecast with parallel processing, comprising: extracting, via a computer, data from a data store, wherein the data is processed to produce forecasting results; servicing, via the computer, a first forecasting module with portions of the data, the first forecasting module processing on a first processing node, the first processing node resolved based on configuration parameters that identify that the first forecasting module is to execute on the first processing node; concurrently servicing a second forecasting module with other portions of the data, the second forecasting module processing on a different or second processing node, the second processing node also resolved based on the configuration parameters that identity that the second forecasting module is to execute on the second processing node; configuring the data based on particular parameters that identify some portions of the extracted data provided as the portions and the other portions that are to be made persistently available in cache so as to not be flushed from the cache to assist when some types of data are repetitively being used by the first and second forecasting modules during different processing states of the first and second forecasting modules; and concurrently producing, via the computer, the forecasting results by the first and second forecasting modules in response to concurrently processing the portions and the other portions of the data on the first and second processing nodes, respectively, and the first and second forecasting modules are duplicate instances of one another and duplicate versions of a same set of forecasting utilities that process in parallel with one another on their respective processing nodes.