1. A method of creating a decision engine including a Bayesian network, comprising: Retrieving data from a client database and forming a focus database, wherein the retrieving includes retrieving data from a static customer database and retrieving data from a data stream; Employing an expectation maximization algorithm to provide a value to valueless records in the focus database; Applying a set of initial rules to the focus database to form at least two nodes; Applying a first learning process to determine a set of arcs to be applied between the at least two nodes; Applying a second learning process to determine a set of states to be applied within each node; Applying a third learning process to determine a set of probabilities applicable to the states learned in the second learning process; and Applying a fourth learning process to update a structure of the at least two nodes, the set of arcs, the set of states within each node, and the set of probabilities for the states.