SAP MDG (Master Data Governance) Test

SAP MDG provides pre-configured data models for domains like Customer, Vendor, Material, and Finance. This skill area assesses the candidate’s ability to work with, extend, and adapt these data models to fit organizational needs. Understanding entity types, attributes, hierarchies, and key mappings is essential to ensure that governance processes support real-world data complexity without breaking SAP’s data integrity rules.

Change Request (CR) processes form the backbone of governance in MDG. This skill evaluates a candidate’s ability to design and manage workflows, use BRF+ for decision logic, and handle multistep approvals. Strong knowledge here enables engineers to enforce accountability, reduce data errors, and ensure that master data changes follow a structured, auditable path before being applied.

This area focuses on how data quality is maintained and improved through validation rules, derivation logic, and monitoring mechanisms within MDG. It is critical to ensure that master data is not only accurate at the point of entry but also remains reliable over time. Candidates are tested on profiling techniques, exception handling, and quality dashboards used to manage trusted data.

SAP MDG must function within complex IT ecosystems. This skill covers techniques for integrating MDG with SAP systems using ALE/IDoc, SOA, or DRF, and with non-SAP platforms using APIs or PI/PO. Proficiency here ensures that governed master data is seamlessly distributed across the enterprise, maintaining consistency and reducing redundancies in operational and analytical systems.

User experience plays a key role in governance adoption. This skill area evaluates knowledge of UI modeling tools like Floorplan Manager (FPM) and SAP Fiori for customizing screens and workflows. Understanding role-based UIs and enhancing usability ensures smooth interaction with governance processes and drives better compliance from business users and data stewards.

While SAP MDG offers standard features, real-world projects often require enhancements. This skill tests knowledge of BAdIs, ABAP enhancements, SMT mapping, and reuse mode. Candidates must be able to create custom logic for validations or derivations, ensuring that governance processes remain business-specific, scalable, and compliant with SAP best practices.

This area focuses on the tools and techniques used to consolidate master data from multiple sources and perform mass updates. Candidates should be able to handle deduplication, harmonization, and batch processing using features like matching rules or file uploads. This skill is vital for organizations undergoing M&A activity, system migrations, or large-scale data cleanups.

Data governance involves controlling who can see or edit specific records or fields. This skill covers role-based access, CR-specific permissions, and field-level restrictions. Strong candidates will know how to secure sensitive master data and align access with organizational roles, ensuring compliance with internal controls and external regulations like GDPR.

This skill tests the candidate’s ability to maintain MDG stability and performance. It includes monitoring workflow execution, diagnosing replication errors, and analyzing logs. Effective troubleshooting ensures quick resolution of data issues, while performance tuning helps MDG scale with enterprise needs. This is essential for support engineers and technical leads in production environments.

This area assesses the candidate’s understanding of aligning MDG workflows with regulatory and internal compliance requirements. It includes audit trail setup, policy enforcement, and integration with tools like SAP Information Steward. Engineers skilled in this area help prevent data breaches, support audit readiness, and maintain strong corporate data governance.

Successful MDG adoption depends on well-executed implementations. This skill covers blueprinting, stakeholder alignment, pilot domain setup, and agile/hybrid delivery models. Knowledge here ensures that candidates can contribute to structured rollouts, avoid rework, and align MDM goals with business outcomes. It’s critical for consultants, architects, and project leads working on MDG transformations.