The Business Rule Framework (BRF+) is the central tool within SAP MDG for defining and managing complex business rules and validations. It allows you to create rules that are triggered during the creation or change of master data, such as making a field mandatory based on the material type. Derivations calculate values, DQM checks data quality post-creation, and Process Steps define workflow actions.

The most effective and granular approach is to configure a rule-based workflow using BRF+. This allows you to define logic that analyzes the change request content. For example, you can set a rule so that only changes to the ‘primary bank account’ or ‘SWIFT code’ trigger the treasury approval step, while updates to a ‘bank contact phone number’ can be auto-approved or follow a simpler path, significantly speeding up low-risk updates.

For mass initial loads, the Data Import Framework (DIF) is the recommended and most efficient tool. It allows you to upload data into staging tables where you can apply various data quality and enrichment rules (like derivations for default values) before the data is formally processed through MDG’s change request workflow. This approach cleanses the data in bulk and ensures it meets system requirements before creation.

MDG allows you to configure the UI for a change request using UIBBs. You can design the UI so that the German user sees and can edit UIBBs related to language-dependent descriptions (like German and English text), while the US user sees UIBBs related to plant-specific scheduling (like MRP type, planning calendar). Both can work on the same, unified change request, but their view and editing capabilities are tailored to their role, ensuring focus and control.

The best proactive and user-friendly approach is to configure a BRF+ derivation for the value help. This derivation can be set to dynamically filter the list of available cost centers to only those that are valid for the previously entered company code. This prevents users from seeing incorrect options in the first place, reducing errors and improving data quality at the point of entry.

This is a classic use case for a BRF+ action (or rule). You can create a rule that says: ‘IF Sales Area = NORTHEAST, THEN SET Account Group = XYZ AND SET Pricing Procedure = ABC’. This action is executed automatically during the processing of the change request, ensuring consistent application of business rules without relying on user input or manual configuration in multiple places.

MDG’s History and Versioning functionality is specifically designed for this purpose. When activated for a data model entity (like Customer or Material), it maintains a version of the master data record each time it is changed via MDG. You can compare any two versions side-by-side to see the exact field-level differences (old value vs. new value), along with the change request ID, timestamp, and user who made the change, providing a robust audit trail.

The Search and Merge process (often part of Consolidation) is specifically designed for this. It involves searching for potential duplicates across source systems based on configurable matching rules (e.g., name, address, tax ID). The system proposes potential matches, and a user or automated rule can then decide to merge these records into a single, golden record in MDG, eliminating duplicates before active consolidation.

This is a perfect scenario for a multi-stage workflow within a single change request. The process can be designed so that Step 1 (general data creation) is completed by the master data team. Upon completion, the workflow automatically creates a new task (Step 2) specifically for maintaining the plant-specific data. This task is assigned directly to the relevant plant manager via the workflow, ensuring clear responsibility, sequencing, and auditability within one unified change request.

The Business Rule Framework (BRF+) is the central tool within SAP MDG for defining and managing complex business rules and validations. It allows you to create rules that are triggered during the creation or change of master data, such as making a field mandatory based on the material type. Derivations calculate values, DQM checks data quality post-creation, and Process Steps define workflow actions.0