A method, computer program product and computer system is disclosed that generates a set of distributed representation vectors from a dataset of textual and non-text data. In one method, a computer system receives a dataset, cleans the received dataset, parses the cleaned dataset to identify known classes of data, extracts data elements from the dataset based on the known classes of data, organizes the extracted data elements into one or more records, compiles a dictionary of unique data elements and associated codes from the one or more records, creates a set of training pairs using permutations of the codes that correspond to data elements within each record, and computes a distributed representation vector for each of the data elements in the dictionary using the set of training pairs.