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Master Data Management (MDM)
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WA1868 Master Data Management (MDM) Bootcamp Training and Courseware
(Coming Soon)
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Enterprises are increasingly recognizing the importance of having a consistent, accurate, authoritative view of their core data sets. This has led to a significant increase in the adoption of Master Data Management (MDM). MDM encompasses data architecture, data modeling, governance processes and data quality policies, data stewardship responsibilities, and alignment between data architecture and business architecture.
This four-day bootcamp provides a deep-dive into Master Data Management (MDM), its core architecture and design activities, as well as strategies and best practices for successful adoption. Lecture content is re-enforced through discussion, group exercises, and hands-on labs designed to build the practical skills necessary to identify, model, and develop the architecture for an MDM initiative. |
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| Topics |
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- MDM Fundamentals
- MDM Value Proposition
- Real World Case Studies
- Risks Associated with MDM
- MDM Infrastructure and Tools
- Metadata Management
- Identifying Master Data
- Modeling Master Data
- Persisting Master Data
- MDM Patterns and Anti-Patterns
- Governing MDM
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| Objectives |
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- Understand the core elements and value propositions involved with MDM
- Examine real world utilization of MDM within an enterprise setting
- Identify and discuss the risks associated with MDM
- Explore the infrastructure and tools involved in MDM
- Gain hands-on experience identifying, modeling, and implementing MDM solutions
- Understand the role and importance of metadata within the context of MDM
- Explore common MDM patterns, anti-patterns, and discuss their application within a broader solution architecture
- Examine the critical role that data management, MDM governance, and data stewardship play within a successful MDM adoption effort
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| Audience |
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Data Architects, Data Modelers, and Technology Team Leads
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| Prerequisites |
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Basic understanding of Data Management and Data Modeling
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| Duration |
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Four Days. |
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Course Outline
1. Introduction to Master Data Management
- Objectives
- Defining Master Data
- Qualities of Master Data
- Master Data Management (MDM)
- Common Causes for Unmanaged Data
- MDM Domains
- Industry Standard Domains
- Using Master Data
- Common Implementation Styles
- Consolidation Implementation Style
- Registry or Federation Implementation Style
- Coexistence Implementation Style
- Transactional Hub Implementation Style
- Summary
2. The Master Data Value Proposition
- Objectives
- Business Benefits of MDM
- Benefits of Accurate Data
- Cost Saving and Efficiency
- Better Regulation Compliance
- Better Time to Market
- Mergers and Acquisitions
- Cross-selling Opportunities
- Summary
3. Real Life Case Studies
- Objectives
- Case Study – Better Reporting at Nationwide
- Problem Domain
- MDM Value for Nationwide
- Analyzing Nationwide’s MDM Solution
- Discussion Question
- Case Study – Cost Cutting at Shell Oil
- Problem Domain
- MDM Value for Shell
- Analyzing Shell’s MDM Solution
- Discussion Question
- Case Study – Single Customer View for Canon Europe
- Problem Domain
- MDM Value for Canon
- Analyzing Canon’s MDM Solution
- Discussion Question
- Case Study – Brinker Gets a New Menu
- Problem Domain
- MDM Value for Brinker
- Analyzing Brinker’s MDM Solution
- Discussion Question
- Summary
5. MDM Risks
- Objectives
- Risk Categories
- Technical Risk – Data Model Standardization
- Technical Risk – Tools and Infrastructure
- Technical Risk – Data Architecture
- Technical Risk – Ignoring the Role of Business Processes
- Technical Risk – Testing and Validation
- The Carbon Interfaces
- Human Risk – Change Management
- Human Risk – Communication
- Human Risk – Unrealistic Expectations
- Human Risk – Funding
- Summary
6. Key Success Factors
- Objectives
- Business Stakeholder Involvement
- Data Model Design
- MDM Governance is Essential
- Incremental Adoption
- Summary
7. MDM Infrastructure and Tools
- Objectives
- Infrastructure and Tools Overview
- Enterprise Components
- Run-time Components
- Design-time Components
- Requirements and Recommendations
- Build vs Buy Analysis
- Vendor Selection Criteria
- Summary
8. Introduction to Metadata Management
- Objectives
- What is Metadata?
- How is Metadata Defined?
- Metadata and MDM
- Basic Concepts
- Value Domain
- Metadata and Data Governance
- Summary
9. Data Modeling in MDM
- Objectives
- Introduction to Data Modeling
- Conceptual Data Model
- Logical Data Model
- Physical or Persistent Data Model
- Persistent Data Model in MDM
- What Goes in MDM?
- Relationship Modeling in MDM
- Additional Modeling Activities
- A Few Best Practices
- Summary
10. The Master Data Model
- Objectives
- Enterprise Data Modeling
- Data Model Types
- The Physical Data Model
- Deriving the Physical Data Model
- Physical Data Model – Scenario #1
- Physical Data Model – Scenario #2
- Physical Data Model – Scenario #3
- The Logical Data Model
- Deriving the Logical Data Model
- Benefits of the Logical Data Model
- Deriving your Logical Model from the Physical
- Designing the Logical Data Model
- The Enterprise Architecture Approach
- EA Approach – Example
- Aligning your Logical and Physical Models
- Alignment Strategies
- The Service Orientation Approach
- SOA Approach – Example
- SOA Alignment with MDM
- The Published Data Model
- The Value for a Published Data Model
- Deriving the Published Data Model
- Industry Standard Data Models
- Summary
11. Designing Your Data Model
- Objectives
- Master Data Model Design Strategies
- Top-down Master Data Design
- Phase 1
- Phase 2
- Phase 3
- Bottom-up Master Data Design
- Phase 1
- Phase 2
- Phase 3
- Merging Domain Models
- Aligning with Existing Data Models
- Summary
12. Persisting Master Data
- Objectives
- MDM Registries
- Dealing with Transactional Master Data
- Working with Data Warehouses
- Working with Datamarts
- Master Data and BI
- Best Practices
- Summary
13. MDM Patterns
- Objectives
- Patterns Structure
- MDM Application Integration Patterns
- Transaction Interception Pattern
- Master Data Publish/Subscribe Pattern
- Message-based Integration Pattern
- MDM Information Integration Patterns
- Data Integration Pattern
- Data Synchronization Pattern
- MDM Enterprise System Deployment Patterns
- Business Intelligence (BI) Pattern
- Data Warehouse Synchronization Pattern
- Summary
14. MDM Anti-Patterns
- Objectives
- Technology-driven MDM
- Fully Canonical MDM
- Big Bang MDM
- Wild West MDM
- Summary
15. Governance and Maturity Model
- Objectives
- Introduction to Governance
- Governance in IT
- Data Governance
- MDM Business Processes
- Metrics
- MDM Maturity Model
- Initial Level
- Reactive Level
- Managed Level
- Proactive Level
- Strategic Performance Level
- Summary
Appendix A – MDM Glossary
Appendix B – MDM Roadmap |
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We regularly offer classes in these and other cities. Atlanta, Austin, Baltimore, Calgary, Chicago, Cleveland, Dallas, Denver, Detroit, Houston,
Jacksonville, Miami, Montreal, New York City, Orlando, Ottawa, Philadelphia, Phoenix, Pittsburgh, Seattle, Toronto, Vancouver, Washington DC.
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