Description
- Module 1: Fundamentals of Reference and Master Data: The fundamental ideas of reference and master data are covered in this section, along with their definitions, distinctions, and significance in data management.
- Module 2: Data Governance: The function of data governance in reference and master data management is examined in this section. It addresses policies, accountability, and data ownership.
- Module 3: Data Architecture: The design and implementation of data architecture for reference and master data are covered in detail in this topic. It addresses concepts including integration, standardization, and data modeling.
- Module 4: Data Stewardship: The management of reference and master data by data stewards is the focal point of this topic. It addresses concepts such as accuracy, consistency, and quality of data.
- Module 5: Data Quality Management: The methods and procedures for guaranteeing the quality of reference and master data are examined in this topic. Moreover, it focuses on validation, monitoring, and data cleansing.
- Module 6: Master Data Management (MDM) Lifecycle: The phases of the MDM lifecycle such as planning, design, implementation, and continuous operation are covered in this section.
- Module 7: Reference Data Management (RDM) Lifecycle: The lifecycle of reference data management is covered in this topic.
- Module 8: MDM and RDM Tools and Technologies: The technologies and tools available for managing reference and master data are discussed in this section.
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