Data Classification Definition

Data classification is the process of analyzing structured or unstructured data and organizing it into categories based on file type, contents, and other metadata. Data classification helps organizations respond to questions such as: Which data do I store? How can I store this data securely? (e.g., where do I have the most important information?) Do I have all the necessary third-party authorization for this sensitive data? This article discusses the basic elements of data classification and provides recommendations for design considerations that will help you create more effective classifications

Purpose of Data Classification

The most important thing you need to know about data classification is that it won't magically improve your collection. It's a foundational, but not necessary step. However, there are certain use cases where classifying data will be critical in your organization's ability to acquire key insights and make decisions.

Data Sensitivity Levels

The idea behind data sensitivity levels is to allow organizations to establish a hierarchy in which they can classify various types of classified or sensitive information. In other words, if a company receives information that is deemed as Classified Level 5 (highest level) then its employees will only be allowed to access it with the proper authorization. There are different levels of classification for different types of data and some go beyond classes. This article will discuss the range of categories used for keeping secrets: