01
MDM Standards
Core Categories
- Data Naming Conventions: Establishes consistent rules for naming entities and attributes to support clarity, searchability, and traceability.
- Data Modeling Standards: Defines how conceptual, logical, and physical models are structured, versioned, and governed.
- Data Stewardship & Ownership: Identifies the roles and responsibilities for managing data quality, lifecycle, and accountability.
- Metadata & Glossary Management: Ensures terms, definitions, and relationships are clearly defined and shared across tools.
- Golden Record & Survivorship Rules: Defines how conflicting data values are resolved to maintain a single source of truth.
- Quality & Validation Rules: Establishes parameters for validating data completeness, accuracy, and conformity.
- Data Lineage & Traceability: Provides visibility into how data flows through systems and transformations.
02
Best Practices
Implementation Best Practices
- Start with critical domains that impact finance, risk, and customer-facing systems.
- Collaborate closely with business data owners and IT architects to align definitions and standards.
- Establish a cross-functional data governance council to review and approve all MDM standards.
- Use a centralized metadata tool to publish and maintain standards documentation.
- Integrate standards enforcement into data pipelines and business processes.
03
Framework
Governance Alignment
MDM standards must be owned and maintained within the data governance framework. This ensures proper oversight, periodic reviews, and integration with compliance requirements such as GDPR, CCPA, and internal audit policies.