1. A computer-implemented method of representing a decision tree data mining model in relational form comprising: accepting a structured query language query referencing a table function, the table function implemented inside a Relational Database Management System and the table function encapsulating creating a decision tree data mining model based on at least one input dataset that is output from at least a portion of the query, wherein the table function receives the input dataset and directly forms a decision tree data mining model, said decision tree data mining model being created, stored and applied inside a database within said Relational Database Management System, wherein application of said decision tree data mining model does not require moving a dataset to a separate data mining engine, by performing steps that are encapsulated in the table function comprising: processing the at least one input dataset to the table function; logically providing a directed acyclic graph based on the at least one input dataset comprising a plurality of nodes and a plurality of links, each link connecting said plurality of nodes; encoding a tree structure by including in each node a parent-child relationship of the node with other nodes; encoding in each node information relating to a split represented by the node, the split information including a splitting predictor and a split value or values; and encoding in each node a target histogram; and generating an output of the directed acyclic graph to form the decision tree data mining model.