13. A method for classifying data, comprising: extracting metadata from one or more relational databases; suggesting classifications based on the metadata; and converting one or more names to normalized labels across an enterprise system based on the suggested classifications, wherein the converting of the one or more names to the normalized labels comprises: analyzing data without a normalized label using lexical name matching by determining a name that is assigned to the data and comparing the name assigned to the data to the one or more normalized labels, wherein if the name appears in the one or more normalized labels, then the one or more normalized labels with the name is added to a list of suggested normalized labels for the data; analyzing data movement operations of data associated with the one or more names to determine if data in one or more locations is the same, wherein if the data is the same, only in different locations, then converting the one or more names associated with the same data to normalized labels based on the suggested classifications; analyzing whether data associated with one or more names without a normalized label contain a same type of content as other data associated with one or more names with a normalized label, wherein if the content is the same then converting the one or more names associated with the same data to normalized labels based on the suggested classifications; and analyzing access logs to determine data that a certain group of users is accessing, wherein one or more names associated with the data that the certain group of users is determined to be accessing is converted to normalized labels based on the suggested classifications.
13. A method for classifying data, comprising: extracting metadata from one or more relational databases; suggesting classifications based on the metadata; and converting one or more names to normalized labels across an enterprise system based on the suggested classifications, wherein the converting of the one or more names to the normalized labels comprises: analyzing data without a normalized label using lexical name matching by determining a name that is assigned to the data and comparing the name assigned to the data to the one or more normalized labels, wherein if the name appears in the one or more normalized labels, then the one or more normalized labels with the name is added to a list of suggested normalized labels for the data; analyzing data movement operations of data associated with the one or more names to determine if data in one or more locations is the same, wherein if the data is the same, only in different locations, then converting the one or more names associated with the same data to normalized labels based on the suggested classifications; analyzing whether data associated with one or more names without a normalized label contain a same type of content as other data associated with one or more names with a normalized label, wherein if the content is the same then converting the one or more names associated with the same data to normalized labels based on the suggested classifications; and analyzing access logs to determine data that a certain group of users is accessing, wherein one or more names associated with the data that the certain group of users is determined to be accessing is converted to normalized labels based on the suggested classifications. 16. The method for classifying data of claim 13 , further comprising confirming the classification is accurate via a verification process.