DATA GOVERNANCE & MASTER DATA MANAGEMENT
Driving Data Quality, Consistency, and Compliance Across the Enterprise
Course Schedule
| Date | Venue | Fees (Face-to-Face) |
|---|---|---|
| 08 – 10 Dec 2025 | Doha, Qatar | USD 2495 per delegate |
Course Introduction
In an increasingly data-driven world, organizations must manage their data as a strategic asset. Without strong governance and control, data becomes inconsistent, inaccurate, and unreliable—leading to poor decision-making, regulatory risks, and inefficiencies.
This intensive 3-day training equips professionals with the tools and frameworks needed to establish robust data governance strategies and implement effective Master Data Management (MDM) programs. Participants will learn how to improve data quality, align data ownership, ensure regulatory compliance, and gain enterprise-wide value from trusted information.
Course Objectives
By the end of this course, participants will be able to:
• Understand the principles and components of data governance and MDM
• Design and implement a data governance framework aligned with business goals
• Establish roles, responsibilities, and data ownership models
• Manage data quality and metadata effectively
• Deploy MDM systems to ensure consistent, accurate, and secure master data
Key Benefits of Attending
• To gain practical knowledge of implementing governance and data management structures
• To support digital transformation and data strategy initiatives
• To meet regulatory compliance obligations (e.g., GDPR, HIPAA, etc.)
• To improve operational efficiency and data-driven decision-making
• To align business and IT stakeholders around shared data accountability
Intended Audience
This program is designed for:
• Data governance leads and data stewards
• IT managers, enterprise architects, and business analysts
• Information and data management professionals
• Compliance, audit, and risk officers
• Digital transformation and analytics teams
Individual Benefits
Key competencies that will be developed include:
• Framework design for enterprise data governance
• Data quality, lineage, and metadata management techniques
• Master data modeling, integration, and lifecycle management
• Policy development and stewardship coordination
• Tools selection and implementation planning
Organization Benefits
Upon completing the training course, participants will demonstrate:
• Ability to build and maintain trusted, high-quality data assets
• Enhanced business agility and analytics capabilities
• Reduction in regulatory and operational risks
• Greater collaboration across departments through shared data ownership
• Structured implementation of enterprise-wide data governance and MDM programs
Instructional Methdology
The course follows a blended learning approach combining theory with practice:
• Strategy Briefings – Foundations of governance, frameworks, MDM models, and compliance standards
• Case Studies – Industry examples of data governance adoption and MDM successes/failures
• Workshops – Hands-on creation of governance charters, stewardship models, and MDM blueprints
• Peer Exchange – Collaborative problem-solving on governance challenges and data quality issues
• Tools – Templates for data policies, stewardship roles, data dictionaries, and governance scorecards
Course Outline
Detailed 3-Day Course Outline
Training Hours: 7:30 AM – 3:30 PM
Daily Format: 3–4 Learning Modules | Coffee breaks: 09:30 & 11:15 | Lunch Buffet: 01:00 – 02:00
Day 1: Fundamentals of Data Governance and Governance Models
Module 1: Introduction to Data Governance (07:30 – 09:30)
• Key concepts, drivers, and goals of data governance
• Common data issues and the business impact of poor data quality
• Governance pillars: ownership, accountability, standards
Module 2: Designing a Governance Framework (09:45 – 11:15)
• Roles and responsibilities: data stewards, owners, committees
• Governance policies, standards, and compliance structures
• Data governance maturity models and roadmaps
Module 3: Workshop – Building a Data Governance Charter (11:30 – 01:00)
• Governance scope and objectives
• Stakeholder roles and reporting structure
• Alignment with business strategy
Module 4: Peer Exchange: Common Governance Pitfalls (02:00 – 03:30)
• Real-world challenges and lessons learned
• Overcoming resistance to governance adoption
Day 2: Master Data Management (MDM) Concepts and Architecture
Module 5: Introduction to Master Data and MDM (07:30 – 09:30)
• What is master data and why it matters
• MDM use cases: customer, product, asset, vendor data
• Types of MDM: registry, consolidation, coexistence, centralized
Module 6: MDM Architecture & Integration (09:45 – 11:15)
• Data modeling and master record creation
• Integration with ERP, CRM, and operational systems
• Data synchronization and version control
Module 7: Workshop – Defining a Master Data Domain Strategy (11:30 – 01:00)
• Identifying key data domains for your organization
• Prioritization based on business value and risk
• Governance around master data changes
Module 8: Tools & Technologies in MDM (02:00 – 03:30)
• Overview of MDM tools and platforms
• Data hubs, golden records, and APIs
• Vendor landscape and selection criteria
Day 3: Data Quality, Compliance & Sustainable Governance
Module 9: Data Quality & Metadata Management (07:30 – 09:30)
• Defining data quality metrics (accuracy, completeness, consistency)
• Data cleansing, profiling, and enrichment techniques
• Metadata, lineage, and cataloging
Module 10: Governance Compliance and Risk Mitigation (09:45 – 11:15)
• Regulatory requirements (e.g., GDPR, HIPAA, CCPA)
• Audit trails, access controls, and data security
• Incident response and policy enforcement
Module 11: Workshop – Governance KPIs and Scorecards (11:30 – 01:00)
• Measuring governance performance
• Data stewardship accountability
• Continuous improvement loops
Module 12: Governance Sustainability & Roadmap (02:00 – 03:30)
• Embedding governance in organizational culture
• Building executive sponsorship
• Long-term governance evolution planning
Certification
Participants will receive a Certificate of Completion in Data Governance & Master Data Management, validating their capabilities in designing, implementing, and managing enterprise-wide data governance and MDM frameworks for sustainable and secure data practices.