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Varonis Moves Beyond Simple Data Classification to Provide a Privacy Perspective

In the data discovery and classification sphere, Varonis has long been associated with impressive features and a user-friendly approach to platform integration. The company takes things a step further by introducing the ability to focus on protection of personal data through a privacy lens.

Varonis’ solutions provide a data-centric modular security platform focused on the primary uses cases of data protection, compliance and privacy, and threat detection and response for both on-premises and cloud unstructured data stores.

Features such as automated performance of privacy assessments as well as automated remediation and retention policies enable Varonis to move beyond rule application and classification of data and support a privacy-centric approach to the organization’s sensitive data. In addition to this, Varonis’ set of over 400 classification rules include those specific to privacy regulatory frameworks such as the GDPR and CCPA. Data subject access requests, a key area of focus for organizations in scope of either of these aforementioned frameworks, can also be automated through Varonis’ product offering.

Source: Varonis Vendor Briefing,

Our Take

As data privacy becomes increasingly prevalent, solutions that may not have extended into the privacy management sphere will look to either better incorporate privacy features or easily integrate with standalone privacy management software big players. Varonis takes the former approach.

The company’s solution builds upon a strong data classification foundation to provide privacy management capabilities through the addition of features to current data permissions controls and rule settings, as well as monitoring of suspicious personally identifiable information (PII) activity. Organizations that leverage the software are then well positioned to decide whether or not their current data security environment necessitates further privacy management and make the appropriate privacy vendor selection accordingly.

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