Data Governance & MDM · 500 chapters

MDM Design & Implementation

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A 500-chapter master course in Master Data Management strategy, architecture, and hands-on implementation.

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500
Chapters
20
Modules
Lifetime
Self-paced access
Global
Enterprise-ready
About the program

What it covers and how it works

Comprehensive, enterprise-grade curriculum covering Master Data Management strategy, architecture, implementation, governance, migrations, and operationalization. Built for self-paced learners and corporate cohorts.

Each topic combines structured lessons with practical, hands-on work and templates you can apply directly. It is self-paced with lifetime access, and available as a instructor-led cohort or private corporate training.

Curriculum

500 chapters across 20 modules

A 500-chapter master course in Master Data Management strategy, architecture, and hands-on implementation.

MODULE 1 - Foundations of Master Data Management (Ch 1-25)
  1. What Is MDM - Definitions & Scope
  2. Why MDM Matters: Business Benefits & Risks
  3. Domains of Master Data: Customer, Product, Supplier, Location, Finance
  4. Principles of Good Master Data: Accuracy, Consistency, Completeness, Uniqueness
  5. Data Quality Fundamentals in MDM Context
  6. Master Data vs Transaction Data vs Reference Data
  7. Metadata, Data Dictionaries & Taxonomies
  8. Data Governance Framework for MDM
  9. Organizational Roles: Data Stewards, Data Owners, MDM Architect
  10. MDM Lifecycle Overview
  11. MDM Use Cases: 360° Customer View, Single Source of Truth
  12. Reference Data Management - Standards & Code Lists
  13. Data Lineage & Provenance in MDM
  14. Data Models: Relational, ER, Graph - For Master Data
  15. Unique Identifiers & Surrogate Keys Strategy
  16. Data Matching & De-duplication Concepts
  17. Identity Resolution & Master Record Linking
  18. Hierarchy Management (Customer & Product hierarchies)
  19. Data Ownership & Stewardship Governance
  20. MDM Policy & Standards Drafting
  21. Change Management & Versioning of Master Data
  22. MDM Program Roadmap Planning
  23. MDM Maturity Models & KPIs
  24. Common Pitfalls & Failures in MDM Initiatives
  25. Capstone: Define MDM Scope & Domain - Mock Project
MODULE 2 - MDM Architecture & Design Patterns (Ch 26-50)
  1. MDM Architectural Styles: Consolidation, Registry, Coexistence, Transactional Hub
  2. Centralized vs Decentralized MDM Architecture
  3. Hybrid MDM Models - When to Use What
  4. Data Integration Patterns for MDM
  5. ETL/ELT vs Real-time Integration for Master Data
  6. Message-based vs Batch Synchronization
  7. Data Hub Architecture: Components & Flow
  8. Hub-and-Spoke vs Bus Architecture
  9. SOA for Master Data Services
  10. API-first vs Database-first MDM Design
  11. Event-driven MDM: CDC & Streams
  12. Reference Data Services & Distribution Layers
  13. MDM in Microservices Architecture - Best Practices
  14. Data Virtualization vs Physical Consolidation
  15. Logical vs Physical MDM Implementation
  16. Data Model Design Patterns (Normalized vs Denormalized)
  17. Schema Evolution & Versioning Strategies
  18. Partitioning, Sharding & Multi-tenant Design
  19. Scalability & Performance Considerations
  20. Governance & Security Layers in MDM Architecture
  21. Data Lineage & Audit Trail Design
  22. High Availability & Disaster Recovery
  23. Multi-region & Multi-cloud Deployment Patterns
  24. Architecture Documentation Standards
  25. Capstone: Draft an MDM Architecture Blueprint
MODULE 3 - Data Integration & Ingestion for MDM (Ch 51-75)
  1. Data Source Identification & Profiling
  2. Data Source Onboarding Process
  3. Source System Connectivity: Databases, Files, APIs, Streams
  4. Data Extraction Methods: Full, Incremental, CDC
  5. Data Transformation & Standardization
  6. Data Mapping & Field-level Mapping Strategies
  7. Data Validation & Cleansing Techniques
  8. Data Enrichment & Reference Data Lookup
  9. Handling Nulls, Defaults & Missing Values
  10. Data Matching & De-duplication Algorithms
  11. Identity Resolution & Matching Thresholds
  12. Survivorship Rules & Conflict Resolution
  13. Hierarchy & Relationship Mapping
  14. Data Merge & Consolidation Workflows
  15. Real-time vs Batch Ingestion for MDM
  16. API-based Ingestion for Master Data
  17. Streaming & Event-driven Ingestion
  18. Data Quality Checks at Ingestion
  19. Logging, Audit Trails & Error Handling
  20. Data Versioning & History Tracking
  21. Incremental Load Strategies
  22. Rollback & Correction Frameworks
  23. Monitoring & Alerting for Integration
  24. Source System Governance & SLAs
  25. Capstone: Build an Ingestion Pipeline for Master Data
MODULE 4 - Data Quality, Cleansing & Standardization (Ch 76-100)
  1. Data Quality Dimensions: Completeness, Consistency, Accuracy, Timeliness
  2. Master Data Quality Rules & Constraints
  3. Data Profiling & Assessment Techniques
  4. Standardization of Formats (Dates, Addresses, Phones)
  5. Parsing & Normalization (Names, Addresses)
  6. Address Validation & Geocoding Integration
  7. Duplicate Detection & Merge Strategy
  8. Data Enrichment (External Datasets)
  9. Hierarchy Clean-up & Consolidation Techniques
  10. Data Validation Automations & Rule Engines
  11. Data Quality Scorecards & Metrics
  12. Data Quality Dashboards & Reporting
  13. Data Correction Workflows - Manual & Automated
  14. Data Stewardship & Change Control for Clean-up
  15. Impact Analysis of Cleansing & Standardization
  16. Audit Logging for Data Quality Changes
  17. Data Governance Approvals & Workflows
  18. Data Quality SLA Definitions
  19. Continuous Data Quality Monitoring
  20. Data Reconciliation Techniques
  21. Handling Legacy Data & Historical Migration
  22. Data Migration Strategy for Clean Master Data
  23. Data Quality in Real-time & Streaming Systems
  24. Master Data Quality Certification & Sign-off
  25. Capstone: Execute a Data Cleansing Project
MODULE 5 - Master Data Modelling & Schema Design (Ch 101-125)
  1. Conceptual, Logical & Physical Data Models
  2. Entity-Relationship Modeling for Master Data
  3. Surrogate Keys, Natural Keys & Composite Keys
  4. Master Record Identifier (MRID) Generation
  5. Handling Hierarchies & Relationships
  6. Multi-domain Master Data Modeling
  7. Metadata & Attribute Modeling
  8. Versioned & Temporal Data Modeling
  9. History & Audit-trail Schema Design
  10. Multi-tenant Master Data Modeling Patterns
  11. Handling Multi-locale & Multi-currency Data
  12. Reference Data & Lookup Tables Modeling
  13. Data Contract Definitions for Entities
  14. Normalization vs Denormalization Tradeoffs
  15. Partitioning, Indexing & Performance-aware Schema
  16. Modeling for Read vs Write Workloads
  17. Modeling for Reporting & Operational Use Cases
  18. Graph-based Master Data Modeling
  19. Hybrid Models: Relational + NoSQL/Graph
  20. Schema Evolution Strategies
  21. Data Dictionary & Data Catalog Maintenance
  22. Semantic Layer & Data Access Abstraction
  23. Data Contracts & API Schema Definitions
  24. Governance Metadata & Lineage in Schema Design
  25. Capstone: Design Full Data Model for Multiple Domains
MODULE 6 - MDM Implementation & Platform Selection (Ch 126-150)
  1. Implementation Approaches: Self-built vs Commercial vs Hybrid
  2. Comparison of Popular MDM Platforms
  3. Cloud-native vs On-Premises - Pros/Cons
  4. Data Store Choices: RDBMS, NoSQL, Graph
  5. Scalability, Performance & Concurrency Considerations
  6. Multi-region & Multi-cloud Deployment Considerations
  7. Data Storage & Indexing Strategies
  8. API Layer Implementation for Master Data Services
  9. Service Contracts & Versioning for APIs
  10. Security, Authentication & Authorization
  11. Governance & Audit Logging Features
  12. Metadata Management & Data Catalog Integration
  13. Workflow Engines & Orchestration for MDM
  14. Data Steward UI/UX: Correction, Merge, Review
  15. Role-based Access Control for MDM Operations
  16. Change Request & Approval Workflows
  17. Audit Trail & Versioning in MDM Systems
  18. Backup, Archival & Disaster Recovery
  19. Data Migration Strategy from Legacy Systems
  20. Integration with Downstream Systems (CRM, ERP, BI)
  21. Incremental Rollout & Phased Implementation
  22. Pilot, PoC & Production Deployment Strategy
  23. Performance Benchmarking & Load Testing
  24. Monitoring & Logging Strategy for MDM
  25. Capstone: Build a PoC MDM Platform Design
MODULE 7 - MDM Governance, Organization & Operations (Ch 151-175)
  1. Governance Structure for MDM Program
  2. Roles & Responsibilities: Stewards, Owners, Admins
  3. Data Policies & Standards for Master Data
  4. Data Lifecycle Policies: Creation, Update, Deletion, Archive
  5. Data Access Policies & RBAC
  6. Change Control & Approval Workflows
  7. Data Stewardship Processes & QA Workflows
  8. Issue Management & Data Correction Workflows
  9. SLA Definitions for Master Data Services
  10. Data Ownership & Accountability Matrix (RACI)
  11. Monitoring & Reporting for MDM Health
  12. KPIs & Metrics for MDM Success
  13. Auditing & Compliance for Master Data
  14. Regulatory Considerations (GDPR, Data Privacy)
  15. Data Retention & Archival Policy Design
  16. Data Versioning & Historical Management Policies
  17. Metadata Governance & Documentation Standards
  18. Change Impact Analysis & Communication Processes
  19. Training & Onboarding for Stewards & Users
  20. Governance for External Data Feeds & Suppliers
  21. Vendor/Third-party Data Governance
  22. Governance for Hybrid / Multi-cloud Environments
  23. Business Continuity & DR Governance
  24. Governance Maturity Model for MDM Programs
  25. Capstone: Draft an MDM Governance Charter
MODULE 8 - Data Migration, Consolidation & Legacy Integration (Ch 176-200)
  1. Legacy Systems Analysis & Data Inventory
  2. Data Profiling & Assessment for Legacy Data
  3. Data Extraction from Legacy Systems
  4. Data Mapping & Transformation Strategy for Migration
  5. Data Cleansing & Standardization Prior to Migration
  6. Duplicate Detection & Merge Strategy for Consolidation
  7. Entity Resolution & Master Record Creation
  8. Historical Data Archival vs Migration Strategy
  9. Phased Migration Planning - Pilot, Rollout, Cut-over
  10. Synchronization & Coexistence Strategies During Migration
  11. Dual-write vs Event-driven Integration During Migration
  12. Data Validation & Reconciliation Post-migration
  13. Data Audit & Quality Checks After Migration
  14. Rollback & Recovery Strategies for Migration Errors
  15. Performance & Load Testing with Migrated Data
  16. Migration Automation Tools & Scripts
  17. Metadata Migration & Data Dictionary Consolidation
  18. Stakeholder Communication & Change Management
  19. Training & UAT for New Master Data System
  20. Interface Updates for Downstream Systems
  21. Monitoring Post-Migration Data Integrity & Quality
  22. Historical Data Cleanup & Archival Strategy
  23. Regulatory Considerations for Data Migration
  24. Documentation & Sign-off for Migration Completion
  25. Capstone: Execute a Master Data Migration Plan
MODULE 9 - Reference Data & Lookup Management (Ch 201-225)
  1. What Is Reference Data vs Master vs Transaction Data
  2. Role of Reference Data in MDM Ecosystem
  3. Reference Data Domains - Codes, Taxonomies, Geographies
  4. Reference Data Lifecycle - Governance, Versioning
  5. Reference Data Services & Distribution Patterns
  6. Centralized Reference Data Management Architecture
  7. Reference Data Integration Across Systems
  8. Standardization & Normalization of Codes & Taxonomies
  9. Hierarchies & Relationships in Reference Data
  10. Translation, Localization & Multi-locale Management
  11. Versioning & Historical Reference Data Handling
  12. Reference Data Quality & Validation Rules
  13. Data Contracts for Reference Data Services
  14. API Design for Reference Data Access
  15. Caching & Performance for Reference Data Services
  16. Synchronization Patterns for Reference Data Updates
  17. Impact Analysis of Reference Data Changes
  18. Reference Data Governance & Stewardship
  19. Auditable Lineage & Change Logging for Reference Data
  20. Metadata Catalog for Reference Data
  21. Reference Data Distribution to Downstream Systems
  22. External Reference Data Feeds - Licensing & Quality
  23. Monitoring & Alerting for Reference Data Consistency
  24. Automated Version Refresh & Synchronization Workflows
  25. Capstone: Build a Reference Data Service
MODULE 10 - Integration with Downstream Systems & Real-Time Sync (Ch 226-250)
  1. Data Publishing Patterns (Push vs Pull)
  2. API Layer for Master Data Distribution
  3. Message Queue / Event-driven Distribution
  4. Real-time vs Batch Sync Strategies
  5. CDC for Downstream Synchronization
  6. Data Contracts & SLAs for Downstream Systems
  7. Schema Evolution Handling in Consumers
  8. Versioning & Backwards Compatibility for APIs
  9. Streaming Updates vs Delta Updates
  10. Notifications & Webhooks for Data Changes
  11. Transactional Consistency & Concurrency Handling
  12. Conflict Resolution Strategies at Consumer Side
  13. Data Subscription & Client Registration Patterns
  14. Monitoring & Logging for Data Distribution
  15. Security, Access Control & Audit for Published Data
  16. Data Masking & Privacy in Data Distribution
  17. Rate Limiting & Throttling for APIs & Streams
  18. Backpressure & Retry Mechanisms
  19. Schema Registry for Consumers
  20. Consumer Onboarding Process for Master Data Services
  21. Data Synchronization Testing & Validation Frameworks
  22. Rollback & Versioning Strategies for Consumers
  23. Cookbook for Data Integration Patterns
  24. Disaster Recovery & Failover for Data Distribution
  25. Capstone: Implement Real-time Master Data Distribution
MODULE 11 - Data Quality Monitoring, Audit & Stewardship (Ch 251-275)
  1. Data Quality Monitoring Framework for MDM
  2. Data Quality KPIs & Metrics for Master Data
  3. Automated Data Quality Checks & Alerts
  4. Data Quality Dashboards & Reporting
  5. Data Quality Issue Management Lifecycle
  6. Data Stewardship Workflows & Tools
  7. Data Correction Logging & Versioning
  8. Audit Trails & Historical Tracking
  9. Data Usage Logging & Access Monitoring
  10. Data Lineage Tracking for Master Data Changes
  11. Privacy & Compliance Logging (GDPR, CCPA)
  12. Metadata Change Management & Version Control
  13. Periodic Data Quality Audits & Reviews
  14. Data Quality SLA Enforcement & Reporting
  15. Training & Certification for Data Stewards
  16. Self-service Data Quality Portal for Business Users
  17. Impact Analysis of Master Data Changes
  18. Remediation Workflows & Notifications
  19. Data Quality Maturity Model & Roadmap
  20. Governance Reporting to Steering Committee
  21. Role-based Dashboards & Visibility
  22. Exception Management & Escalation Procedures
  23. Data Quality Certifications & Badging
  24. Continuous Improvement & Feedback Loops
  25. Capstone: Build a Data Quality Monitoring & Stewardship Framework
MODULE 12 - Master Data Governance, Compliance & Security (Ch 276-300)
  1. Regulatory & Compliance Requirements (GDPR, Data Privacy)
  2. Data Privacy by Design for Master Data
  3. Access Control & Permission Models
  4. RBAC & ABAC for MDM Systems
  5. Data Masking & Anonymization Strategies
  6. Encryption (At-rest & In-transit)
  7. Audit Logging & Traceability for Access & Changes
  8. Secure APIs & Data Access Endpoints
  9. Data Retention & Deletion Policies
  10. Consent Management & Data Subject Rights
  11. Data Residency & Cross-border Governance
  12. Vendor & Third-party Data Integration Compliance
  13. Governance for External Data Feeds
  14. Privacy Impact Assessments (PIA)
  15. Security & Compliance Monitoring & Reporting
  16. Incident Management & Breach Response
  17. Disaster Recovery & Business Continuity Planning
  18. Governance Documentation & Policy Maintenance
  19. Governance Training & Awareness Programs
  20. Compliance Audit Readiness for Master Data
  21. Governance Maturity Assessment & Roadmap
  22. Governance Review Board & Steering Committee Functions
  23. Data Ethics & Responsible Use of Master Data
  24. Third-party Certification & Standards for MDM
  25. Capstone: Draft a Complete MDM Governance & Compliance Plan
MODULE 13 - Metadata Management, Data Catalogs & Lineage (Ch 301-325)
  1. What Is Metadata - Business, Technical & Operational
  2. Importance of Metadata in MDM & Data Ecosystem
  3. Data Catalog Concepts & Benefits
  4. Building a Metadata & Data Catalog Strategy
  5. Metadata Standards & Taxonomies
  6. Data Lineage: Concepts & Why It Matters
  7. Metadata Capture at Ingestion & Consumption Layers
  8. Automated vs Manual Metadata Capture
  9. Tagging & Classification of Master Data Entities
  10. Data Dictionary Maintenance & Versioning
  11. Data Lineage Visualization Tools & Approaches
  12. Impact Analysis for Schema or Reference Data Changes
  13. Metadata-driven Data Quality Rules
  14. Data Catalog Governance & Ownership
  15. Integration of Metadata with Governance Policies
  16. Data Catalog API & Search Interface Design
  17. Data Discovery & Self-Service for Business Users
  18. Reference Data & Master Data Catalog Integration
  19. Metadata Lifecycle & Archival Strategy
  20. Metadata Security & Access Controls
  21. Metadata Change Management & Audit Trails
  22. Metadata as a Service (MaaS) in Enterprise Architecture
  23. Metadata-driven Data Operations (Monitoring, Alerts)
  24. Cross-system Lineage & Enterprise Traceability
  25. Capstone: Build a Metadata Catalog + Lineage Plan
MODULE 14 - Master Data Analytics, Reporting & Data Products (Ch 326-350)
  1. Use Cases - 360° Views, Unified Reporting, Analytics
  2. Data Warehouse / Data Lake Integration with MDM
  3. Master Data in Data Warehouses & Analytical Models
  4. Slowly Changing Dimensions & Historical Data
  5. Master Data Quality Impact on Analytics
  6. Data Warehouse Schema Integration with Master Data
  7. Data Mart Design with Master Data Foundation
  8. Lakehouse vs Graph/NoSQL for Hierarchical Data
  9. Reference Data & Master Data in Reports
  10. Data Consistency & Synchronization in Reporting Systems
  11. Real-time Master Data Feeds for BI
  12. Data Products Definition & Lifecycle
  13. API-based Data Products for Consumers
  14. Versioning & Backwards Compatibility for Data Products
  15. Data Contract Enforcement for Reporting Consumers
  16. Data Lineage & Auditability for Regulatory Reports
  17. Data Sharing & Collaboration Patterns
  18. Self-service Analytics with Trusted Master Data
  19. Data Governance for Reporting & Data Products
  20. Metadata-driven Reporting Pipelines
  21. Master Data Publishing Workflows
  22. SLOs & SLAs for Data Products
  23. Data Product Monitoring & Usage Metrics
  24. Documentation & Data Collateral for Consumers
  25. Capstone: Build a Data Product Lane Using MDM
MODULE 15 - MDM in Big Data & Cloud-Native Environments (Ch 351-375)
  1. Challenges of Master Data in Big Data / Distributed Systems
  2. Master Data at Scale - Partitioning & Sharding
  3. Handling Master Data in Streaming & Event-driven Systems
  4. Master Data with Data Lakes, Lakehouses & Data Mesh
  5. Cloud-native MDM Patterns & Best Practices
  6. Data Consistency & Distributed Transactions
  7. Multi-region & Global Master Data Sync
  8. Hybrid On-prem + Cloud MDM Deployments
  9. API / Microservices Architecture for Master Data Services
  10. Serverless Data Services for Master Data
  11. Data Replication & Sync across Systems & Clouds
  12. Versioning & Conflict Resolution in Distributed Systems
  13. Data Partitioning & Locality Considerations
  14. DR & HA for Cloud MDM
  15. Compliance & Data Residency in Multi-region Architecture
  16. Data Encryption & Security in Cloud MDM
  17. Cloud Cost Optimization for MDM at Scale
  18. Data Integration Patterns in Cloud-native Ecosystems
  19. Metadata and Lineage in Distributed Architectures
  20. Monitoring & Observability in Cloud MDM Systems
  21. Performance & Latency for Master Data APIs
  22. Design Patterns for High-volume Transactions
  23. Governance & Access Control in Cloud-native MDM
  24. Vendor & Third-party Data Integration in Cloud MDM
  25. Module 15 Lab: Design a Cloud-native MDM Architecture
MODULE 16 - Master Data Lifecycle Management & Versioning (Ch 376-400)
  1. Data Lifecycle Phases: Creation, Update, Merge, Archive, Deletion
  2. Versioning Strategies for Master Data
  3. Temporal Tables & History Tables Implementation
  4. Audit Trail Design for Master Data Changes
  5. Change Request Workflow & Approval Systems
  6. Data Correction vs Update vs Merge - Best Practices
  7. Data Archival Strategies & Cold Storage
  8. Purge, Data Retention & Compliance Requirements
  9. Soft Deletes vs Hard Deletes - Tradeoffs
  10. Merge, Split, Decommissioning Entities - Policies
  11. Data Lineage & Impact Analysis for Lifecycles
  12. Notifications & Alerts for Data Changes
  13. Data Deprecation & Sunset Strategies
  14. Consumer System Synchronization on Changes
  15. Version Compatibility & Backwards Compatibility
  16. Historical Data Querying & Reporting
  17. Rolling Upgrades & Schema Evolution Handling
  18. Data Recovery & Rollback Mechanisms
  19. Data Migration Strategies for Schema Changes
  20. Documentation & Metadata for Lifecycle Events
  21. Data Retention Compliance & Audit Requirements
  22. Lifecycle Governance & Stewardship Policies
  23. Metrics & KPIs for Master Data Lifecycle Health
  24. Continuous Improvement & Data Quality Over Time
  25. Capstone: Design Master Data Lifecycle Management Plan
MODULE 17 - MDM Testing, Validation & QA (Ch 401-425)
  1. Importance of Testing in MDM Projects
  2. Unit Testing for Data Transformations
  3. Integration Testing for Ingestion & Distribution
  4. Regression Testing for Master Data Changes
  5. Data Quality Test Suites & Automation
  6. Validation of Matching & De-duplication Algorithms
  7. Testing Hierarchy & Relationship Integrity
  8. Testing Referential Integrity & FK Constraints
  9. Schema Evolution Testing & Compatibility Checks
  10. Performance Testing for MDM Workloads
  11. Load Testing & Scalability Benchmarks
  12. Concurrency & Conflict Testing for Updates
  13. Security & Access Control Testing
  14. Data Migration Testing & Validation
  15. Mock Data Generation for Testing
  16. Test Data Management & Versioning
  17. Automated Testing Frameworks for MDM
  18. CI/CD Integration of Tests for MDM Pipelines
  19. Test Reporting & Quality Dashboards
  20. Issue Tracking & Remediation Workflow for Test Failures
  21. Governance & Approval Gates on Quality Tests
  22. Periodic Testing & Regression Schedules
  23. Documentation of Test Cases & Results
  24. User Acceptance Testing (Business Stakeholders)
  25. Capstone: Build a Full Testing Suite for MDM System
MODULE 18 - Change Management, Adoption & Org Integration (Ch 426-450)
  1. Change Management Strategy for MDM
  2. Stakeholder Mapping & Communication Plan
  3. User Onboarding & Training Programs
  4. Roles, Responsibilities & RACI for Governance
  5. Business Process Integration with Master Data Workflows
  6. Cross-department Collaboration & Data Ownership
  7. Adoption Metrics & Success KPIs
  8. Incentives & Accountability for Data Owners
  9. Continuous Training & Knowledge Base Maintenance
  10. Data Literacy & Metadata Awareness Programs
  11. Support & Helpdesk for Master Data Users
  12. Feedback Loops for Data Issues & Improvements
  13. Governance Board & Regular Review Meetings
  14. Data Ownership Transfer & Onboarding of New Systems
  15. Documentation, Guidelines & Policy Publication
  16. Audit & Compliance Reporting for Stakeholders
  17. Internal Communications & Change Updates
  18. Versioning & Rollout Strategy for Changes
  19. Legacy System Sunset & Migration Planning
  20. Scaling MDM across Business Units & Geographies
  21. Cultural Change Management & Governance Culture
  22. Executive Buy-in & Sponsorship Strategy
  23. Cost-Benefit Monitoring & ROI Tracking
  24. Continuous Improvement Roadmap for MDM Program
  25. Capstone: Create MDM Adoption & Change Management Plan
MODULE 19 - Enterprise MDM Projects: Case Studies & Industry Patterns (Ch 451-475)
  1. Retail: Product Master Data & SKU Management
  2. E-commerce: Customer Master & Order Data Consolidation
  3. Manufacturing: Supplier, Material & BOM Master Data
  4. Healthcare: Patient & Provider Master Data
  5. Banking: Customer, Account, KYC Master Data
  6. Telecom: Subscriber, Device & Network Master Data
  7. Logistics: Asset, Location & Vendor Master Data
  8. Public Sector: Citizen & Asset Master Data Governance
  9. Energy: Asset, Meter & Site Master Data
  10. Insurance: Policy, Customer & Claims Master Data
  11. SaaS: Tenant, User & Product Master Data
  12. Media: Content, User & Rights Master Data
  13. Travel: Customer, Booking & Property Master Data
  14. Real Estate: Property, Owner & Portfolio Master Data
  15. Education: Student, Staff & Course Master Data
  16. Cross-industry Patterns & Best Practices
  17. Common Challenges & Failure Cases
  18. Lessons from Large-scale MDM Implementations
  19. Compliance & Regulatory-driven MDM Projects
  20. Vendor / Partner Data Integration Challenges
  21. Cloud vs On-premises MDM Migration Stories
  22. Data Governance Maturity Growth Stories
  23. Multi-generation Data Model Migration Case Studies
  24. Master Data Monetization & Data Products
  25. Capstone: Document an Industry-specific MDM Plan
MODULE 20 - Capstones, Templates, Certification & Program Closure (Ch 476-500)
  1. Capstone Program Overview & Assessment Criteria
  2. Template Pack: Data Models, Catalogs, Dictionaries
  3. Template Pack: Data Contracts & API Specs
  4. Template Pack: Governance Policies & Standards
  5. Template Pack: Data Quality Rules & Dashboards
  6. Template Pack: Reference Data Service Templates
  7. Template Pack: Migration & Onboarding Checklists
  8. Template Pack: Stewardship & Workflow Templates
  9. Template Pack: Security & Compliance Policy Templates
  10. Template Pack: Data Lifecycle & Retention Templates
  11. Template Pack: Testing & CI/CD Automation Templates
  12. Template Pack: Data Product & API Templates
  13. Template Pack: Documentation & Training Templates
  14. Final Project: Build & Deploy Full MDM System
  15. Final Project: Real-world Data Migration & Consolidation
  16. Final Project: Data Quality Monitoring & Stewardship Setup
  17. Final Project: Data Catalog, Metadata & Lineage Implementation
  18. Final Project: Data Product & API Deployment Using MDM Hub
  19. Final Project: Reference Data Service Implementation
  20. Final Project: Security, Compliance & Access Control
  21. Final Project: CI/CD, Testing & Automation for MDM
  22. Final Project: Governance & Change Management Plan
  23. Certification Exam & Evaluation Process
  24. Graduation, Certification & Badging
  25. Future Roadmap: Evolving Data Standards & MDM Trends
Program formats

How you learn

Self-paced

Lifetime access as a reference you return to as your program matures.

Cohort-based

Instructor-led cohorts with live discussion and reviews.

Enterprise

Private, tailored delivery for your organization and tooling.

Exam-focused

Where a certification applies, preparation aligned to the current official curriculum.

Related programs

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FAQ

MDM Design & Implementation - answered

What is the MDM Design & Implementation program?

A 500-chapter master course in Master Data Management strategy, architecture, and hands-on implementation. It runs to 500 chapters across 20 modules.

How is the program delivered?

Each topic combines structured lessons with practical, hands-on work and templates you can apply directly. It is self-paced with lifetime access, and available as a instructor-led cohort or private corporate training.

Who is it for?

Data governance leads, data stewards, MDM practitioners, architects, and data offices - from practitioners deepening a specialism to teams standing up a program.

Do I need prior experience?

Some programs assume a data background; others build from first principles. Each is structured so motivated learners can follow the full arc from foundations to advanced practice.

Is there a downloadable brochure?

Yes. A PDF brochure summarizing the full curriculum is available from the download button at the top of this page.

Does it include certification?

It awards a Durga Analytics certificate of completion. Where a topic maps to an external certification, preparation follows the current official curriculum.

Is it self-paced or cohort-based?

Both. Self-paced with lifetime access is standard; instructor-led cohorts and private enterprise delivery are also available.

Can my organization run this privately?

Yes. It can be delivered as a private corporate cohort tailored to your organization, tooling, and maturity. Contact us to scope it.

How does it relate to the other governance programs?

It is part of the Data Governance & MDM track, which spans enterprise governance (with a data quality masterclass and open-source lab folded in), CDMP certification, MDM design and Informatica, and data strategy. Each is standalone and they complement each other.

How do I enrol or request details?

Use the contact form to request program details or a corporate cohort, and a senior practitioner will respond.

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Enrol as an individual with lifetime access, or bring the program to your team as a tailored corporate cohort.

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