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EIM 302 – Understanding and Implementing Master Data Management

Duration: 3 – 5 days

This course teaches the concepts, techniques, and approaches to building a master data management program for any organization and will provide a plan for implementing master data management throughout an enterprise.

Master Data Management

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Description

Master data is a collection of key objects around which the business processes of an enterprise can be modeled and analyzed. Master data can include structured data elements, such as commonly used entities, attributes, hierarchy definitions, and unstructured data elements, such as business rules, document structure, logos, and report formats. Sharing data and relating it to other data is also a challenge when the organization does not know its master data and the metadata associated with it, and does not understand the relationship between metadata and information intelligence.

This course teaches the concepts, techniques, and approaches to building a master data management program for any organization and will provide a plan for implementing master data management throughout an enterprise.

This class is a workshop since concepts are assimilated more easily when they are practiced. The workshops are built around actual case studies of an organization interested in developing and implementing a master data management program.

Objectives

  • Develop a master data management strategy for an organization
  • Develop an approach for metadata and data governance and stewardship within master data management
  • Learn how to work collaboratively and the benefits of sharing experiences and solutions to metadata issues and concerns

Seminar Content

  • Understanding Master Data
    • Defining master data
    • Technical master data
    • Business master data
    • Master data and its relationships to metadata
  • Concepts and Principles of Master Data Management
    • Data Model
    • Historical Archiving
    • Aggregation and Hierarchies
    • Workflow and Process Modeling
    • Data Quality
    • Unstructured Data
    • Access to Information
    • Business and Technical Collaboration
    • Distribution and Data Sharing
    • Service Oriented Architecture (SOA)
  • How to Implement a Master Data Management Program
    • Master Data Management Project Plan
    • Creating the Metadata Project Plan
  • Metadata ROI Definition
  • Challenges of Implementing a Master Data Management Program
  • Components of a Master Data Management Program
  • Constructing the Master Data Management Program Scope Document
  • Defining Metadata Requirements for a Master Data Management Program
  • Identifying Sources of Master Data
  • Integrating Sources of Master Data through Metadata
  • Roles in Master Data Management
  • Approaches to Master Data Management Program Development
  • Understanding the Key Master Data Management Vendors
    • Evaluating Master Data Management Tools (integration and access)
    • How to Evaluate Master Data Management Tools Vendors
  • Metadata Repository Architecture as part of Master Data Management
    • Centralized, Decentralized, and Distributed
  • Introduction to Data Governance and Stewardship
    • Data Governance Overview
    • Roles in Data Governance
    • Alignment of data governance and Master Data Management program
  • Implementing the Master Data Management Strategy
    • Implementation issues
    • Successful strategy situations
    • Role of People, Process and Technology in MDM
  • Workshop Conclusion
    • Summary, additional exercises, sources for further reading, etc.

About the Course Designer

This training was designed by David Marco, PhD, an internationally recognized authority on data and AI governance, to help teams succeed in real organizational conditions. The curriculum equips participants with practical judgment, shared language, and decision clarity that hold under scale, risk, and executive accountability.

David Marco PHD EWSolutions

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