Sensitive Data Discovery & Classification

Data classification is a way of tagging data according to its type, sensitivity, and value to the organization if altered, stolen, or destroyed. This process is integral to the protection of data, as policies can be built based on how certain data is classified and its level of sensitivity. While the specificity of types of classification can vary, the most common types of data classification include public data, private and/or internal data, confidential data, and restricted data.

Taking a more traditional manual approach to data classification is incredibly labor-intensive, time-consuming, and prone to human error. By contrast, automated data classification streamlines the classification process by automatically analyzing and categorizing data in real-time. This automated classification is carried out based on predetermined parameters, which are set by data teams in advance and allowed to run as new data enters a given data ecosystem.

An effective data discovery software should provide teams with a few key capabilities. These include an automated data discovery and classification process, giving enterprises clear visibility across their ecosystem as new data sources are added to different components. This software should also reduce costs and time-to-data, as well as reduce the risk of data breaches and leaks and ensure the compliance with various applicable data laws and regulations.