1. A machine-based method comprising receiving historical multi-dimensional data representing multiple source variables to be used as an input to a predictive model of a commercial system, the source variables including nominal variables or ordinal variables, assigning a status to each source variable, the status comprising the variable being a predictor primary variable or a transformed variable or having transformations applied in a variable definition field; applying a first set of transformations to the source variables, the first set of transformations being selected to increase predictive power, and applying a second set of transformations to the data, the second set of transformations being selected based on strength of measurement represented by a variable.