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SAP C_MDG_90 Exam covers various topics that include data modeling, master data governance architecture, data quality, data replication, and more. C-MDG-90 exam consists of 80 questions that must be completed within 180 minutes. The questions are multiple-choice and cover both theoretical and practical aspects of SAP Master Data Governance. Candidates must achieve a passing score of 65% to earn the SAP Certified Application Associate - SAP Master Data Governance certification.
Reference: https://training.sap.com/certification/c_mdg_90-sap-certified-application-associate---sap-master-data-governance-g/
The C_MDG_90 Exam is intended for application consultants, support consultants, project managers, and anyone who seeks to implement and customize the master data governance solutions in a business environment. C-MDG-90 exam tests the candidate’s knowledge on various aspects of SAP Master Data Governance, including data quality, data governance, replication scenarios, and more. Additionally, the C_MDG_90 Exam also evaluates the candidate’s ability to leverage best practices, identify customer-specific requirements, and recommend solutions to improve business processes.
Preparing for the SAP C-MDG-90 certification exam requires a sound understanding of SAP Master Data Governance principles, tools, and methodologies. Candidates should have a deep understanding of the SAP MDG solution configuration and administration, including its data modeling, replication, and validation procedures. Holding this certification demonstrates a professional's proficiency in SAP Master Data Governance, making them eligible to work as a consultant, developer, or project manager in the SAP Master Data Governance domain.
To be eligible for the SAP C_MDG_90 certification exam, candidates must have a minimum of two years of experience working with SAP Master Data Governance. They should also be proficient in SAP ERP and SAP S/4HANA systems and have a good understanding of data modeling concepts.
SAP C-MDG-90 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Data Quality and Analytics | 8%-12% | - Data Quality Management
- 1. Analytics and Reporting
- 2. Validation Rules
- 3. Data Quality Monitoring
- 4. Duplicate Check
|
| Topic 2: Consolidation and Mass Processing | >12% | - Consolidation
- 1. Data Consolidation
- 2. Mass Processing
- 3. Data Harmonization
|
| Topic 3: Custom Objects and Solution Extensions | 8%-12% | - Extensibility
- 1. Business Logic Enhancements
- 2. Custom Data Models
- 3. UI Extensions
|
| Topic 4: MDG Change Request Process Implementation | 8%-12% | - Workflow and Governance
- 1. Workflow Configuration
- 2. Change Request Types
- 3. Business Rules
|
| Topic 5: MDG Project Execution | <8% | - Implementation Methodology
- 1. Testing and Deployment
- 2. Project Planning
- 3. Best Practices
|
| Topic 6: Data Load and Import | <8% | - Data Migration
- 1. Migration Validation
- 2. Import Framework
- 3. Initial Load
|
| Topic 7: Domain Specific Capabilities | >12% | - Master Data Domains
- 1. Supplier
- 2. Material
- 3. Customer
- 4. Business Partner
- 5. Financial Master Data
|
| Topic 8: MDG Overview and Architecture | >12% | - MDG Architecture
- 1. Data Models
- 2. Deployment Options
- 3. Governance Processes
|
| Topic 9: Data Replication and Key Mapping | 8%-12% | - Replication Framework
- 1. DRF Configuration
- 2. Key Mapping
- 3. Integration Scenarios
|