Data Theft

Sensitive data discovery and classification is a process used to identify and categorize sensitive or confidential information within an organization's digital assets.

Data lacking a pre-defined model of organization or that does not follow one. Such data is often text-heavy, but can also include facts, figures and time and date information. The resulting irregularities and ambiguities make unstructured data much harder for programs to understand than data stored in databases with fields or documents with annotations. Many estimates claim unstructured data comprises the vast majority of global data, and that this category of data is growing rapidly.