1. A computer-implemented method for normalizing an in-memory representation of stored data for faster superscalar processing, the method comprising: accessing stored data that includes multiple columns, each column having a data type; selecting a column in the accessed data to determine an appropriate in-memory representation; determining a data type of the selected column; determining whether row data associated with the selected column can be normalized based at least in part on the determined data type of the selected column; determining a fixed size value for a normalized data representation, wherein the fixed sized value is sized such that it can be processed by a superscalar processor as a single instruction; and upon determining that the row data can be normalized, converting the row data associated with the selected column into the normalized data representation, wherein the normalized data representation is a format that allows performing parallel processing of multiple instances of the normalized data representation using the superscalar processor and that represents multiple data types as the determined fixed size value that can be processed by the superscalar processor in the single instruction, wherein the preceding steps are performed by at least one processor.