1. A data mining method, comprising: providing a computing system comprising a computer readable medium and a plurality of computing devices electrically coupled through an interface apparatus, wherein a data mining modeling algorithm, a plurality of parameter algorithms, and test data are stored on said computer readable medium, wherein said test data comprises a known outcome associated with a marketing offer, and wherein each computing device of said plurality of computing devices comprises at least one central processing unit (CPU) and an associated memory device; receiving, by each computing device of said plurality of computing devices, a copy of a database managing software application; first receiving, by said computing system, a first steady data stream from a plurality of client spreadsheets; first dividing, by the computing system, said first steady data stream into a first plurality of data subsets; associating, by the computing system, each data subset of said first plurality of data subsets with a different customer number associated with a different customer; first placing, by the computing system, a different data subset of said first plurality of data subsets in each said associated memory device, wherein said first receiving, said first dividing, and said first placing are performed simultaneously; selecting a technique for generating a data mining model applied to each of said first plurality of data subsets; distributing simultaneously, said data mining modeling algorithm using said selected technique to each said computing device; distributing a different parameter algorithm of said plurality of parameter algorithms to each said computing device; executing, each said different parameter algorithm on said data mining modeling algorithm located on each said computing device; adjusting simultaneously in response to said executing, an associated parameter setting for each said data mining modeling algorithm in each said computing device, wherein each said associated parameter setting comprises a different parameter setting; running simultaneously, each said data mining modeling algorithm comprising said associated parameter setting on a different associated data subset of said first plurality of data subsets using said selected technique to generate first data mining models on said computing devices, wherein a first associated data mining model of said first data mining models is stored on each of said computing devices comparing each of said first data mining models on each of said computing devices to said test data to determine a best selection data mining model of said first data mining models; determining, a best data mining modeling algorithm comprising a best parameter setting from said data mining modeling algorithms comprising said associated parameter settings in accordance with said selected technique, wherein said best data mining modeling algorithm is the data mining modeling algorithm that is associated with said best selection data mining model, and wherein said best data mining modeling algorithm is a neural network algorithm; and first removing each different data subset of said first plurality of data subsets from each said associated memory device; after said first removing, second receiving by said computing system, a second steady data stream differing from said first steady data stream; second dividing, by the computing system, said second steady data stream into a second plurality of data subsets; second placing, by the computing system, a different data subset of said second plurality of data subsets in each said associated memory device, wherein said second receiving, said second dividing, and said second placing are performed simultaneously; simultaneously applying said best data mining modeling algorithm to each data subset of said second plurality of data subsets; generating in response to said simultaneously applying, second data mining models on said computing devices, wherein a second associated data mining model of said second data mining models is stored on each of said computing devices, wherein an output of each of said second data mining models comprises a numerical description representing an expected behavior for customers, and wherein each of said second data mining models is associated with a mortgage company; and comparing each of said second data mining models on each of said computing devices to each other data mining model of said second data mining models to determine a best data model of said second data mining models, wherein said best data model comprises a most predictive data model having a highest degree of correlation to an offer with respect to a customer of said customers as compared to all other data models of said second data mining models.