1. A computer-implementable method for identifying information within a data repository, comprising: selecting variables of interest within the data repository to provide selected variables; defining a depth of interactions of interest with respect to the variables of interest to provide a defined depth of interactions; applying an optimal experimental design operation to the selected variables and the defined depth of interactions, the applying comprising determining a design matrix based upon the optimal experimental design operation; selecting, using at least one query, a sample case from the data repository, the at least one query being based on the design matrix, wherein a computational effort associated with selecting the sample case from the data repository is independent of a size of data in the data repository, and is dependent on a prediction model associated with selecting the sample case; loading the sample case into the design matrix, resulting in a sample matrix of the data repository; and performing modeling operations based on the sample matrix of the data repository.