Dig Security

A multi-cloud data security platform that discovers, classifies, and protects sensitive data assets across various cloud environments.

Multi-Cloud Proprietary Cloud Service Only
Category Data Security & Encryption
Last page update 18 days ago
Pricing Details Contact for pricing information.
Target Audience Organizations managing sensitive data across multiple cloud environments.

Dig Security manages managing and securing sensitive data across multiple cloud environments, a problem exacerbated by the complexity and sprawl of modern cloud deployments. This agentless multi-cloud data security platform leverages a robust data classification engine to discover, classify, and protect sensitive data assets, including both structured and unstructured data.

Technically, Dig Security employs a cloud-native approach, integrating with major cloud providers such as AWS, Azure, GCP, and Snowflake. It utilizes automated classifiers for various regulatory standards (PCI, PII, PHI, GDPR, CCPA, etc.) to ensure compliance and highlight data misconfigurations, access anomalies, and vulnerabilities. The platform's real-time data detection and response (DDR) capabilities enable immediate alerts and responses to suspicious activities, integrating with existing security workflows to enhance incident handling.

Operationally, Dig Security simplifies the management of cloud data security posture by providing a unified policy engine that governs data across different cloud services. It prioritizes findings based on context to reduce alert fatigue and offers comprehensive reports for data teams and owners, enhancing compliance assurance and risk management. However, the scalability of real-time monitoring can be limited by the volume of data and the complexity of the cloud environment, potentially leading to increased costs and resource requirements.

Specifically, Dig Security's automated discovery and classification processes can handle dozens of database types, and its continuous monitoring ensures sub-minute granularity in detecting data-related incidents. While this provides excellent visibility and control, it also necessitates careful resource planning to avoid performance degradation and cost spikes, especially in large-scale, multi-account setups.

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