DOT

ARCAD DOT is a data anonymization and subsetting solution designed to secure sensitive information while preserving functional data quality for development, testing, analytics, and training environments. It enables organizations to comply with privacy regulations by masking personal data consistently and intelligently. The platform ensures realistic, coherent datasets that maintain referential integrity, supporting secure DevOps workflows and reducing risks associated with using production data outside production systems.

Features

• Advanced data masking for structured and unstructured datasets.
• Consistent anonymization preserving referential integrity across systems.
• Configurable masking rules for personal, financial, and proprietary data.
• Data subsetting to generate smaller, compliant test environments.
• Automated workflows to anonymize large data volumes efficiently.
• Support for IBM i, relational databases, and hybrid system landscapes.
• Audit-ready reporting for compliance and governance.

Capabilities

• Creation of privacy‑compliant datasets without altering functional behavior.
• Scalable processing for high‑volume enterprise data landscapes.
• Integration with DevOps pipelines for secure CI/CD testing cycles.
• Selective data extraction to tailor datasets to specific test scenarios.
• Rule-based anonymization templates reusable across teams and systems.
• Multi-environment synchronization ensuring masking consistency.
• Flexible deployment across on‑prem, cloud, and hybrid setups.

Benefits

• Reduced data privacy risk by eliminating exposure of real personal data.
• Faster and safer testing cycles using realistic but anonymized datasets.
• Lower infrastructure costs through optimized, subsetted environments.
• Improved compliance with GDPR, HIPAA, and internal security policies.
• Higher developer productivity with readily available secure test data.
• Streamlined audits thanks to standardized, traceable masking processes.
• Enhanced security posture across teams working with non‑production data.