Curriculum
12 Sections
51 Lessons
8 Weeks
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Module 1: Introduction to SAP S/4HANA MDG
4
1.0
Overview of SAP S/4HANA MDG: Key concepts and benefits
1.1
Understanding master data and its importance
1.2
MDG architecture and components
1.3
Integration of MDG with SAP S/4HANA and other systems
Module 2: Data Governance Framework
4
2.0
Principles of data governance
2.1
Data stewardship and ownership
2.2
Data quality management: Standards and practices
2.3
Data lifecycle management: Creation, maintenance, and retirement
Module 3: MDG Data Models
4
3.0
Designing MDG data models: Key considerations
3.1
Configuring MDG data models for different master data domains (e.g., materials, customers, suppliers)
3.2
Customizing data models to meet business requirements
3.3
Managing hierarchies and relationships in data models
Module 4: Data Quality Management
4
4.0
Techniques for ensuring data accuracy and consistency
4.1
Data validation rules and error handling
4.2
Data cleansing and enrichment strategies
4.3
Monitoring and improving data quality
Module 5: MDG Workflow and Change Request Management
4
5.0
Configuring MDG workflows: Process design and implementation
5.1
Managing change requests: Types, processes, and approvals
5.2
Workflow monitoring and error handling
5.3
Enhancing workflow efficiency and effectiveness
Module 6: Integration with SAP S/4HANA
4
6.0
Integration scenarios and methods with SAP S/4HANA modules (e.g., FI, MM, SD)
6.1
Data replication: Methods and tools
6.2
Managing data interfaces with external systems
6.3
Troubleshooting and resolving integration issues
Module 7: Data Replication and Distribution
4
7.0
Methods for data replication across systems and environments
7.1
Configuring data distribution processes
7.2
Handling data synchronization and consistency
7.2
Best practices for data replication and distribution
Module 8: MDG Analytics and Reporting
4
8.0
Analyzing MDG processes and performance
8.1
Creating and customizing MDG reports and dashboards
8.2
Leveraging SAP Fiori for MDG analytics
8.3
Interpreting and acting on data insights
Module 9: Best Practices and Case Studies
4
9.0
Case studies of successful MDG implementations
9.1
Lessons learned from real-world scenarios
9.2
Best practices for implementing and managing MDG
9.3
Industry-specific considerations and strategies
Module 10: Hands-On Projects
6
10.0
Project 1: Designing and configuring an MDG data model for a specific master data domain
10.1
Project 2: Implementing and managing an MDG workflow and change request process
10.2
Project 3: Setting up data replication and integration with SAP S/4HANA
10.3
Project 4: Developing MDG analytics and reporting solutions
10.4
Final project: Comprehensive MDG implementation for a real-world client
10.5
Peer review and feedback sessions
Module 11: Advanced Topics in MDG
3
11.0
Exploring advanced MDG features and functionalities
11.1
Customizing MDG for complex business scenarios
11.2
Future trends in master data governance and SAP S/4HANA
Module 12: Career Development and Placement Support
6
12.0
Preparing for MDG roles: Resume writing, LinkedIn optimization
12.1
Building a professional portfolio: Showcasing your MDG projects and skills
12.2
Interview preparation: Common questions and best practices
12.3
Networking strategies: Building connections in the data governance field
12.4
Job search assistance: Leveraging job boards, recruiters, and more
12.5
100% placement assistance: Connecting with potential employers
SAP S/4HANA MDG
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