Data Classification

Start with the Most Comprehensive Data Classification

Digital Guardian data classification can automatically locate and identify your sensitive data then apply labels to classify and determine how the data is handled. Our comprehensive data classification solutions - from automated content and context-based classification to manual user classification - are optimized for regulatory compliance, intellectual property protection, and mixed environments.By understanding what sensitive data you have, where it is, and how it’s used, you’re in a better position to apply the appropriate controls

The Most Comprehensive Data Classification Solution
Digital Guardian incorporates the full range of classification from fully automated to manual user
classification. Digital Guardian’s unique, context-based classification can automatically identify and tag
sensitive data even before you develop policies. Our automated contentbased file inspection identifies,
tags and fingerprints sensitive data for the lowest false positives. User classification empowers users to
classify sensitive data based on business requirements. Each can be used singly, or combined to deliver the
most comprehensive data classification solution.

Key Benefits

Get Rapid Time to Value Digital Guardian automated classification drives repeatability and predictability. It also speeds
implementation time by enabling you to classify even before formal policy creation. And DG User
Classification integrates natively in Office applications for minimal change in workflows.

Drive More Efficient Security Digital Guardian classification organizes and prioritizes
data, enabling organizations to proactively assign data protection resources to the most valuable data. This
ultimately drives more efficient security.

Use Data Classification as an Enabler
“In effect, data classification enables a less restricted handling of most data by bringing clarity to the items
requiring the elevated control.”
- Gartner, Understanding Insider Threats Published: May 2, 2016, Erik
T. Heidt, Anton Chuvakin