1. A computer-implemented method of profiling a data set in a parallel processing environment, comprising: partitioning an initial data set stored in a row based format vertically according to multiple attribute subsets, wherein partitioning comprises extracting data for the multiple attribute subsets from the initial data set; storing the extracted data for the multiple attribute subsets in a plurality of staging files, the plurality of staging files including extracted data that is static; profiling the multiple attribute subsets based on a specific attribute value, wherein different staging files are provided to different machines in a plurality of machines for profiling; determining a set of row identifiers that satisfy the specific attribute value identified in the profiling of the different staging files processed on the plurality of machines; extracting, for each row identifier in the set of row identifiers, a row identifier, a column identifier, and a value of an attribute for a set of columns associated with each row identifier; merging the row identifier, the column identifier, and the value of the attribute for the set of columns associated with each row identifier to form a profiled subset of the initial data set; and transmitting, displaying or storing the profiled subset of the initial data set, a further processed version, or combinations thereof.