DATPROF

Automatically scans databases and data stores to identify, locate, and classify sensitive personally identifiable information (PII) and protected health information (PHI) across the organization. Uses pattern matching and machine learning to detect sensitive data elements without manual inventory.

Masks sensitive data elements in real-time or batch mode using configurable masking rules and algorithms (redaction, tokenization, encryption, shuffling). Applies masking policies consistently across databases while maintaining data utility for testing.

Implements granular access controls that determine which users and teams can access which masked or subset datasets. Enforces data access policies based on roles, projects, and compliance requirements.

Creates smaller, representative subsets of production databases that maintain referential integrity and data relationships while reducing volume. Enables faster provisioning of test environments with production-like data without copying entire datasets.

Automates the provisioning and deployment of masked and subset test data to development, QA, and staging environments. Orchestrates the entire workflow from source selection through environment refresh with version control and audit trails.

Provides pre-built, industry-specific compliance templates for GDPR, HIPAA, PCI-DSS, and other regulatory frameworks. Automatically applies appropriate masking rules, retention policies, and data handling procedures based on selected compliance standards.

Maps data flows and dependencies across systems to show where sensitive data originates, how it moves through the organization, and what systems depend on it. Enables impact analysis when applying masking or retention policies.

Provides a centralized interface for creating, configuring, testing, and managing data masking rules. Supports multiple masking algorithms (redaction, tokenization, encryption, shuffling, format-preserving encryption) with rule versioning and reusability.

Records all data access, masking operations, and provisioning activities with detailed audit trails. Generates compliance reports demonstrating adherence to regulatory requirements and data handling policies.

Coordinates masking, subsetting, and provisioning operations across multiple heterogeneous databases and data sources simultaneously. Maintains consistency and referential integrity across distributed data environments.

Defines and enforces data retention policies based on regulatory requirements and business rules. Automatically identifies and purges data that exceeds retention periods while maintaining audit trails of deletion.