Enterprise Enablement Services for DataMasque

Combining direct technical delivery with targeted organizational and stakeholder engagement, this service is for organizations seeking to implement, extend, or operationalize DataMasque data masking in enterprise environments.

Scope covers technical build and enterprise integration, including direct collaboration with compliance, legal, business, and technical teams to review risk, define requirements, map data flows, and align with organizational processes. The service includes discovery and classification of sensitive data, development and configuration of reusable architectures, and integration with AWS services. Knowledge transfer is delivered through documentation, runbooks, mentoring, and internal showcases, preparing staff for sustainable operation.

The approach can be tailored to any stage of a client’s DataMasque journey.

Work covers both the technical build and the enterprise integration needed to make it credible and sustainable:

Engaging the organization

• Direct interaction with compliance and legal teams to review existing risk assessments, identify gaps, and clarify their expectations of the masking solution, translating regulatory obligations (GDPR, PCI DSS, HIPAA, local laws) into practical requirements for implementation.
• Workshops with application owners, developers, DBAs, infrastructure, QA and business stakeholders to map data flows, define masking priorities, and document operational constraints that shape delivery.
• Definition of masking scope and integration points with enterprise processes such as change management, release governance, and security controls.

Designing and implementing the solution

• Discovery of sensitive data using DataMasque's automated tools and manual methods across AWS RDS, self-managed databases hosted on EC2, or third-party AMIs (e.g. Oracle, SQL Server, PostgreSQL, Db2, Sybase)
• Extension of masking coverage to structured files types such as CSV, XML, JSON, Parquet, and fixed-width, as well as Mainframe VSAM datasets accessible via Amazon S3.
• Development of reusable YAML rule sets built on DataMasque’s task_definitions, rule_definitions, and mask_definitions framework for modular, maintainable, and extensible masking logic.
• Configuring masking jobs, deterministic and randomised functions, and automation to support repeatable, consistent and scalable masking across applications and environments.
• Establishing integration points with AWS services (e.g. RDS, S3, EC2) and development/test data pipelines.

Enabling the client team

• Production of detailed documentation, reusable configuration patterns, operational runbooks and reference configurations.
• Mentoring sessions with DBAs, developers, testers and compliance staff to embed knowledge and establish repeatable practices.
• Support for building internal technical showcases using the client’s own data and applications, demonstrating value and driving adoption across teams.

Outcome: An operational enterprise-ready implementation of DataMasque on AWS, delivered with reusable configurations, operational automation, and real environments. This is supported by a framework that enables future extension, stakeholder alignment, and sustainable operation by internal teams.