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WA1869 Governing Master Data Management (MDM) Training and Courseware (Coming Soon)

Master Data Management (MDM) provides a powerful collection of tools, processes, techniques and patterns for addressing data quality and data consistency issues. In the absence of governance, however, the potential of MDM can be quickly overrun by the associated implementation costs. Additionally, there is a high risk of interrupting mission-critical systems and processes while rolling out an MDM strategy. All of this points to a need for structure, proven adoption procedures, and methodical risk mitigation strategies – in short, a need for governance.

This two-day workshop explores MDM and the importance of implementing governance around such a crucial initiative. The adoption of a rigorous process for describing the current and future states of an enterprise’s maturity as well as defining a progressive roadmap should not be done in an ad-hoc fashion.  This course will equip managers, architects, and team leads with a clear understanding of the challenges and risks associated with MDM adoption as well as key strategies to mitigate these risks.  Significant attention will also be given to the proper way to engender organizational change, champion the MDM initiative, and best practices around managing master data, metadata, business processes, and ensuring alignment with strategic objectives. MDM can be adopted incrementally, contractually managed by policies, and matured over time alongside the natural evolution of the enterprise. The key to this is governance. 

Lecture topics in this workshop are reinforced through lively discussion and collaborative group exercises.

Course Outline

1. MDM Basics

• Objectives
• What is Master Data?
• Qualities of Master Data
• Common causes of Unmanaged Data
• MDM Domains
• Identifying Master Data
• Metadata vs Master Data
• Summary 

2. Governance Fundamentals

• Objectives
• The Need for Governance
• Formal Governance Methodologies
• MDM Governance Elements
• MDM Governance Procedures
• MDM Governance Policies
• MDM Governance Metrics
• Structure for MDM Governance
• Core Governance Artifacts
• Governance Best Practices
• Summary

3. Contractual Governance

• Objectives
• Policies, Contracts, and SLAs
• Data Stewardship
• Sample Data Management Contract
• Governance by Policy
• Data Management Policies
• Data Quality Policies
• Summary 

4. Governance Models

• Objectives
• Models for Governance
• The Governance Monarchy
• The Governance Duopoly
• The Governance Federation
• The Governance Dictatorship
• Anarchy as Governance
• Matrix-style Governance Models
• Navigating Governance Models
• 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. Implementing MDM Governance

• Objectives
• Implementation Strategies
• Heavy vs Thin Governance
• Champions and Stewards
• MDM Centers of Excellence (CoE)
• Types of CoE
• Best Practices for Implementing an MDM CoE
• Summary 

7. MDM Funding Models

• Objectives
• The Problem with Funding MDM
• Identifying Different Funding Models
• Model #1: Incremental, Self-funded
• Model #2: Corporate Tax
• Model #3: Strategic Enterprise Initiative
• Model #4: Charge-back Funding
• Comparing the Models
• Summary 

8. MDM Governance Maturity Models

• 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

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