Before a data loss prevention (DLP) system can protect data, it must first know what data is sensitive (and what kind of sensitive). Data classification is the all-important prerequisite for data protection; without it, the system will be flying blind with no basis for detecting risks and enforcing policies. It is also one of the most time-consuming and error-prone aspects of traditional DLP deployments.
Accurate data classification is the cornerstone to any successful data protection program. However, traditional data classification methodologies have failed to adequately address the broad majority of critical enterprise data and assets.
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