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ICT & Digital Skills

Master Data Management (MDM) Strategies Training

Master Data Management (MDM) Strategies Training equips professionals with the frameworks, tools, and governance practices needed to design, implement, and sustain enterprise-wide master data programmes. Participants explore data quality management, MDM architecture patterns, and integration strategies that drive trusted, consistent data across the organisation. This course bridges business and IT perspectives, enabling delegates to lead MDM initiatives that deliver measurable value.

⏱ 5 Days 📡 In-Person 🎯 Intermediate From KES 80,000

About This Course

In today's data-driven economy, organisations that cannot trust their core data — customers, products, suppliers, employees, and assets — face compounding risks: duplicated records, inconsistent reporting, failed regulatory audits, and poor strategic decisions. Master Data Management (MDM) is the discipline that establishes a single, authoritative source of truth for critical business entities, ensuring every system and every stakeholder works from the same verified foundation.

This five-day intensive programme by TrainingComplex provides a comprehensive grounding in MDM strategy, governance, architecture, and implementation. Delegates will move from understanding why MDM matters to designing practical solutions: selecting the right MDM implementation style, building data stewardship structures, defining data quality rules, and integrating master data across cloud and on-premises environments. Real-world case studies from retail, financial services, healthcare, and public sector contexts bring every concept to life.

The course balances conceptual rigour with hands-on application. Delegates will work through MDM maturity assessments, data modelling exercises, governance charter templates, and integration design scenarios. By the final day, each participant will have drafted a roadmap they can take back and begin executing within their own organisation.

Whether you are an IT architect designing the technical backbone of an MDM solution, a data analyst struggling with inconsistent reference data, or a business leader sponsoring a data quality initiative, this training provides the shared language and practical toolkit your team needs to succeed.

Who Should Attend

Learning Objectives

Course Modules

Module 1: Foundations of Master Data Management

  • Defining master data: what it is and what it is not
  • The MDM business case: cost of poor data quality
  • MDM versus reference data, transactional data, and metadata
  • Key master data domains: customer, product, supplier, location, employee
  • MDM in the context of enterprise data strategy and data governance
  • MDM maturity models and organisational readiness assessment

Module 2: MDM Implementation Styles and Architecture Patterns

  • Registry, consolidation, coexistence, and centralised hub styles explained
  • Selecting the right implementation style for your business context
  • MDM hub-and-spoke versus federated architecture models
  • Cloud-native MDM versus on-premises deployment considerations
  • Multi-domain MDM architecture design principles
  • Aligning MDM architecture to enterprise integration patterns

Module 3: Master Data Modelling and Domain Design

  • Conceptual, logical, and physical data modelling for MDM
  • Designing the customer master data model: attributes, hierarchies, and relationships
  • Product master data model: classification, enrichment, and lifecycle states
  • Supplier and location domain modelling best practices
  • Managing complex party hierarchies and organisational structures
  • Extending the MDM data model to accommodate business change

Module 4: Data Governance for MDM

  • Establishing a data governance framework aligned to MDM objectives
  • Defining data ownership: data owners, stewards, and custodians
  • Drafting data policies, standards, and definitions for master data domains
  • Data stewardship workflows: creation, change, and retirement of master records
  • Governance committee structures and escalation mechanisms
  • Measuring and reporting governance effectiveness

Module 5: Data Quality Management in MDM

  • The six dimensions of data quality: accuracy, completeness, consistency, timeliness, validity, and uniqueness
  • Data profiling techniques: column analysis, pattern matching, and relationship discovery
  • Root cause analysis for master data quality failures
  • Designing data quality rules and validation logic
  • Data quality scorecards and remediation workflow design
  • Continuous data quality monitoring and alerting strategies

Module 6: Data Matching, Deduplication, and Golden Record Creation

  • Deterministic versus probabilistic matching techniques
  • Confidence scoring and match threshold configuration
  • Survivorship rules: selecting the best attribute value across source records
  • Building and maintaining golden records across data domains
  • Handling near-duplicate and potential match queues in stewardship workflows
  • Testing and tuning matching algorithms for accuracy and performance

Module 7: MDM Integration Architecture

  • Integration patterns for MDM: real-time, batch, event-driven, and API-based
  • Connecting MDM hubs to ERP, CRM, and cloud SaaS platforms
  • Designing canonical data models for cross-system interoperability
  • Master data syndication: publishing golden records to downstream consumers
  • Handling data lineage, traceability, and audit trails across integrations
  • Error handling, exception management, and reconciliation in MDM integration

Module 8: MDM Platform Evaluation and Selection

  • Overview of leading MDM platforms: SAP MDG, Informatica MDM, Reltio, Stibo STEP, and others
  • Defining functional and non-functional requirements for MDM tools
  • Build versus buy versus SaaS considerations for MDM solutions
  • Conducting a structured platform evaluation using a requirements scorecard
  • Vendor assessment: support, scalability, licensing models, and roadmap alignment
  • Proof-of-concept design and evaluation criteria for MDM platform selection

Module 9: MDM Implementation Planning and Change Management

  • Phased MDM implementation approach: foundation, expansion, and optimisation
  • Defining MDM programme scope, objectives, and success metrics
  • Stakeholder mapping and engagement strategy for MDM initiatives
  • Change management frameworks applied to data governance and MDM adoption
  • Building a cross-functional MDM team: roles, skills, and responsibilities
  • Common MDM implementation pitfalls and how to avoid them

Module 10: Building the MDM Business Case and Roadmap

  • Quantifying the cost of poor master data quality for executive audiences
  • Identifying and prioritising MDM use cases by business impact
  • Cost-benefit analysis and ROI modelling for MDM investment
  • Crafting an executive-level MDM business case and value narrative
  • Developing a 12-to-36-month MDM implementation roadmap
  • KPIs, milestones, and governance checkpoints for MDM programme success

Requirements & Prerequisites

Participants should have a working familiarity with databases, data management concepts, or enterprise business systems. Experience in a data-related role — such as data analysis, IT architecture, business intelligence, or data governance — is recommended. No prior MDM platform certification is required, though a basic understanding of how data flows between enterprise systems will help delegates get the most from the programme.

Training Methodology

Organisational Benefits

Where Is Master Data Management (MDM) Strategies Training Offered?

This course runs in-person across: Accra, Johannesburg, Dar es Salaam, Riyadh, Mombasa, Lagos, Cape Town, Kampala, Kigali, Naivasha, Nairobi, Abuja, Dubai, Pretoria, Arusha, Nakuru, Zanzibar, Kisumu, Addis Ababa, plus Live Virtual (online) cohorts. Browse live dates for your city below.

Upcoming Schedules

LocationFormatDatesPrice
Live Virtual Online 12 Oct 2026 – 16 Oct 2026 KES 80,000
Accra, Ghana In-Person 26 Oct 2026 – 30 Oct 2026 USD 3,800
Johannesburg, South Africa In-Person 26 Oct 2026 – 30 Oct 2026 USD 3,500
Dar es Salaam, Tanzania In-Person 26 Oct 2026 – 30 Oct 2026 USD 2,300
Riyadh, Saudi Arabia In-Person 26 Oct 2026 – 30 Oct 2026 USD 4,500
Mombasa, Kenya In-Person 26 Oct 2026 – 30 Oct 2026 KES 120,000
Lagos, Nigeria In-Person 26 Oct 2026 – 30 Oct 2026 USD 2,500
Cape Town, South Africa In-Person 26 Oct 2026 – 30 Oct 2026 USD 3,800
Kampala, Uganda In-Person 26 Oct 2026 – 30 Oct 2026 USD 1,900
Kigali, Rwanda In-Person 26 Oct 2026 – 30 Oct 2026 USD 1,900
Naivasha, Kenya In-Person 26 Oct 2026 – 30 Oct 2026 KES 120,000
Naivasha, Kenya In-Person 2 Nov 2026 – 6 Nov 2026 KES 120,000
Nairobi, Kenya In-Person 2 Nov 2026 – 6 Nov 2026 KES 105,000
Accra, Ghana In-Person 2 Nov 2026 – 6 Nov 2026 USD 3,800
Abuja, Nigeria In-Person 2 Nov 2026 – 6 Nov 2026 USD 2,800

+227 more dates — view live schedule →

Frequently Asked Questions

Do I need a technical background to attend this course?

A basic understanding of enterprise data systems or data management concepts is recommended, but the course is designed for both business and IT professionals. The programme deliberately bridges technical and business perspectives so that architects, analysts, governance leads, and project managers can all participate meaningfully.

Will this course cover specific MDM software tools?

Yes. Module 8 is dedicated to evaluating leading MDM platforms including SAP MDG, Informatica MDM, Reltio, and Stibo STEP. The course is platform-agnostic overall, focusing on strategies and principles that apply regardless of the tool your organisation uses or is considering.

Is a certificate awarded upon completion?

Yes. Participants who attend the full five-day programme and complete the required activities will receive a TrainingComplex Certificate of Completion in Master Data Management Strategies, which can be used for professional development records and continuing education portfolios.

Can my organisation arrange a private cohort tailored to our specific MDM context?

Absolutely. TrainingComplex offers in-house delivery of this programme, which can be customised to focus on your organisation's specific data domains, platforms, and strategic priorities. Contact our training consultants to discuss scheduling, group rates, and customisation options.

What should I bring or prepare before attending?

Delegates are encouraged to come with a basic understanding of how data flows between systems in their organisation and, if possible, examples of master data quality challenges they currently face. No special software installation is required — all tools and templates used during the course will be provided by TrainingComplex.

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