ADVANCED DATA MANAGEMENT
Mastering Enterprise Data Governance, Quality, Architecture & Analytics for Strategic Advantage
Course Schedule
| Date | Venue | Fees (Face-to-Face) |
|---|---|---|
| 08 – 12 Jun 2026 | Dubai, UAE | USD 3495 per delegate |
Course Introduction
As organizations generate and collect ever-growing volumes of data, effective data management becomes critical for strategic success. Poor data quality, siloed systems, and lack of governance can compromise decision-making, compliance, and digital transformation. This advanced course provides the frameworks, tools, and best practices needed to manage enterprise data as a strategic asset.
Participants will explore advanced concepts in data governance, metadata management, master data management (MDM), data quality frameworks, architecture standards, and analytics integration. The course combines technical depth with a business-aligned approach to ensure data adds measurable value.
Course Objectives
By the end of this course, participants will be able to:
• Design and implement enterprise-wide data governance frameworks
• Apply data quality rules, scorecards, and cleansing processes
• Build metadata and master data management (MDM) programs
• Align data architecture with business objectives and compliance needs
• Leverage data assets for advanced analytics, AI, and business intelligence
Key Benefits of Attending
• Gain strategic and technical insight into enterprise-grade data management
• Learn how to align IT, compliance, and business teams around shared data goals
• Access global best practices in governance, lineage, and architecture
• Reduce risk through better data quality, control, and documentation
• Support digital transformation and analytics initiatives with a solid data foundation
Intended Audience
This program is designed for:
• Data governance and data management professionals
• Chief Data Officers, Data Architects, and IT Managers
• Business intelligence and analytics leaders
• Risk, compliance, and audit professionals handling data oversight
• Digital transformation and enterprise system project teams
Individual Benefits
Key competencies that will be developed include:
• Data stewardship, governance design, and stakeholder engagement
• Metadata tagging, business glossaries, and lineage documentation
• Master data model design and integration strategies
• Data quality measurement, remediation, and automation
• Support for AI/ML, BI dashboards, and data-as-a-service models
Organization Benefits
Upon completing the training course, participants will demonstrate:
• Improved data quality and governance across business units
• Better compliance with regulations like GDPR, HIPAA, and BCBS 239
• Standardized definitions, ownership, and reporting across systems
• Reduced costs through clean, accurate, and deduplicated data
• Enhanced data-driven decision-making across operations and strategy
Instructional Methdology
The course follows a blended learning approach combining theory with practice:
• Strategy Briefings – Global trends, frameworks, and regulatory impacts
• Case Studies – Enterprise data management challenges and resolutions
• Workshops – Build data governance charters, quality dashboards, and metadata catalogs
• Peer Exchange – Lessons learned from digital transformation and BI deployments
• Tools – Governance templates, quality scorecards, MDM models, architecture diagrams
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: Data Governance Foundations
- Module 1: Enterprise Data Strategy and Governance Models (07:30 – 09:30)
• Business alignment, governance frameworks (DAMA-DMBOK, DCAM) - Module 2: Roles and Responsibilities in Data Governance (09:45 – 11:15)
• Data owners, stewards, committees - Module 3: Policies, Principles, and Charters (11:30 – 01:00)
• Data ethics, usage rules, enforcement - Module 4: Workshop – Create a Data Governance Charter (02:00 – 03:30)
• Define roles, principles, and governance scope
Day 2: Metadata & Master Data Management (MDM)
- Module 5: Metadata Management Essentials (07:30 – 09:30)
• Business glossaries, technical metadata, lineage - Module 6: Cataloging Tools and Lineage Tracking (09:45 – 11:15)
• Automation, APIs, metadata repositories - Module 7: MDM Design and Implementation (11:30 – 01:00)
• Entity modeling, match/merge logic, hierarchy management - Module 8: Workshop – Build a Metadata & MDM Use Case (02:00 – 03:30)
• Scenario planning and tool mock-up
Day 3: Data Quality Frameworks
- Module 9: Dimensions of Data Quality and Profiling (07:30 – 09:30)
• Accuracy, completeness, consistency, timeliness - Module 10: Data Cleansing and Standardization Techniques (09:45 – 11:15)
• Rules engines, de-duplication, data profiling - Module 11: Dashboards and Scorecards (11:30 – 01:00)
• KPIs, remediation workflows, tracking - Module 12: Workshop – Create a Data Quality Dashboard (02:00 – 03:30)
• Select indicators and develop reporting visuals
Day 4: Data Architecture and Compliance
- Module 13: Enterprise Data Architecture Design (07:30 – 09:30)
• Layered architecture, warehouses, lakes, lakeshores - Module 14: Cloud vs On-Premise Data Platforms (09:45 – 11:15)
• Security, scalability, integration - Module 15: Regulatory Alignment and Risk Mitigation (11:30 – 01:00)
• GDPR, CCPA, BCBS 239, internal audit - Module 16: Workshop – Map an Enterprise Data Architecture (02:00 – 03:30)
• Draw architecture aligned to business case
Day 5: Advanced Analytics and Data Monetization
- Module 17: Enabling AI/ML Through Data Readiness (07:30 – 09:30)
• Data labeling, quality thresholds, data lakes - Module 18: Data Democratization and Self-Service BI (09:45 – 11:15)
• Governed access, data catalogs, BI tools - Module 19: Building a Data Operating Model (11:30 – 01:00)
• Process ownership, team structure, SLAs - Module 20: Final Workshop – Design a Data Management Roadmap (02:00 – 03:30)
• Strategic initiatives, quick wins, maturity stages
Certification
Participants will receive a Certificate of Completion in Advanced Data Management, confirming their ability to architect, implement, and govern enterprise data ecosystems that meet strategic, operational, and compliance needs.