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Quest Training

Multi-Domain Master & Reference Data Management Training Course

Shows how to manage master and reference data across customer, supplier, product, asset and staff domains, with hubs, matching, survivorship and ERP roll-out.

DQS · Data Quality & Master Data ManagementAll Levels#3029ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Data, Analytics & Digital TransformationCategories:Data Quality & Master Data Management

Course Overview

This advanced practical course develops the capabilities required to implement master and reference data management across multiple domains, including customer, supplier, product, material, asset, employee, and location data. Rather than treating master data as one topic within a broader framework or limiting it to customer records, the programme follows the full implementation path from domain scoping to a trusted golden record that ERP, finance, procurement, and reporting processes can rely on. Participants will examine how to distinguish master, reference, and transactional data, design domain data models and hierarchies, and select an appropriate hub style, whether registry, consolidation, coexistence, or centralized. The course explains how cross-reference keys and integration patterns keep source systems and the hub aligned. The programme also covers the core techniques of record matching, merging, and survivorship, together with the ownership, stewardship, and approval workflows that govern how master records are created, changed, and retired. Data quality is treated as an input to matching and stewardship, while attention is given to supplier controls, reference code lists, and ERP migration and roll-out. Through practical exercises, participants will prioritize master data domains, choose hub styles, design match and survivorship rules, build create-and-change workflows, and develop a phased roadmap for implementing and sustaining enterprise master data management.

Learning Objectives

  • Distinguish master, reference, transactional, and metadata and their roles in business processes.
  • Identify and prioritize master data domains according to business value, risk, and complexity.
  • Design domain data models, attributes, relationships, and hierarchies for enterprise master data.
  • Evaluate registry, consolidation, coexistence, and centralized hub styles for each domain.
  • Define cross-reference keys and integration patterns between source systems and the hub.
  • Manage reference data code lists, classifications, mappings, and version control.
  • Design deterministic and probabilistic matching rules with suitable thresholds.
  • Develop survivorship rules that produce and maintain a trusted golden record.
  • Establish domain ownership, stewardship roles, and decision rights for master data.
  • Design create, change, and retire workflows with appropriate approvals and controls.
  • Plan master data cleansing, migration, and reconciliation for ERP implementations.
  • Develop a phased roadmap for implementing and sustaining multi-domain master data management.

Who Should Attend

This course is designed for Master Data Managers, Data Management Leads, ERP Functional Consultants, Data Stewards, Procurement and Supplier Master Data Teams, Finance Master Data Specialists, and Data Governance Professionals. It is also suitable for Data Architects, Integration Specialists, Business Analysts, ERP Programme Managers, Asset and Materials Data Coordinators, HR Systems Specialists, and managers responsible for customer, supplier, product, asset, or employee records. The programme is particularly relevant to banks, oil and gas companies, ministries, and other organizations implementing or consolidating ERP systems, preparing customer and supplier data for e-invoicing, or establishing an enterprise master data function.

Learning Outcomes

  • Classify enterprise data into master, reference, and transactional categories.
  • Prioritize master data domains using a structured value and risk assessment.
  • Design domain data models and hierarchies that support business processes.
  • Select an appropriate hub style and integration pattern for each domain.
  • Maintain reference code lists and mappings under controlled versioning.
  • Configure matching rules that balance false positives and false negatives.
  • Apply survivorship rules to assemble and maintain golden records.
  • Assign domain ownership, stewardship responsibilities, and decision rights.
  • Implement controlled workflows for creating, changing, and retiring master records.
  • Strengthen supplier master data controls against duplicates and payment fraud.
  • Plan master data migration, cleansing, and reconciliation for ERP roll-outs.
  • Develop an actionable roadmap for sustaining multi-domain master data management.

Course Outline

Day 1

Master & Reference Data Foundations

  • Master, reference, transactional, and metadata distinctions.
  • Customer, supplier, product, asset, employee, and location domains.
  • Reference data: ISO country and currency codes.
  • Business impact of duplicate master records.
  • Mapping where master data is created and used.
  • Critical master data attributes per domain.
  • Assessing master data maturity and pain points.
  • Prioritizing domains by value, risk, and complexity.
  • Building the master data business case.
  • Practical Application: Map master data creation points in a selected organization and prioritize three domains.
Day 2

Domain Models, Hub Styles & Integration

  • Domain entities, attributes, and relationships.
  • Party models for organizations, individuals, and roles.
  • Legal-entity, product, asset, and location hierarchies.
  • Registry, consolidation, coexistence, and centralized hub styles.
  • Selecting a hub style by domain and landscape.
  • Cross-reference keys across source systems.
  • Batch, real-time, and event-based integration.
  • Reference data mappings, versioning, and distribution.
  • Operational versus analytical master data management.
  • Practical Application: Select and justify a hub style and integration pattern for supplier and product data.
Day 3

Matching, Merging & Golden Record Survivorship

  • Standardizing names, addresses, and identifiers.
  • Data quality profiling results as a matching input.
  • Deterministic and probabilistic matching.
  • Blocking keys, match scores, and thresholds.
  • Managing false positives and false negatives.
  • Survivorship by source trust, recency, and completeness.
  • Attribute-level precedence and golden record assembly.
  • Steward review queues for uncertain matches.
  • Unmerge handling, lineage, and audit trails.
  • Practical Application: Design match and survivorship rules for a duplicated customer and supplier dataset.
Day 4

Master Data Ownership, Governance & Workflows

  • Domain ownership, stewardship, and decision rights.
  • Master data policies, standards, and naming conventions.
  • Create, change, and retire request workflows.
  • Supplier onboarding: tax and bank details verification.
  • Segregation of duties and duplicate payment prevention.
  • Customer, product, and asset creation approvals.
  • Service levels for master data requests.
  • Stewardship metrics and dashboards.
  • Change control for reference code lists.
  • Practical Application: Design a supplier create-and-change workflow with roles, approvals, controls, and service levels.
Day 5

ERP & MDM Roll-Out and Sustainment

  • Phasing the roadmap by domain and business unit.
  • Master data in ERP implementations and consolidations.
  • Cleansing, de-duplication, loading, and reconciliation.
  • Cut-over planning and readiness checks.
  • Customer and supplier identifiers for e-invoicing.
  • Aligning MDM with national data management standards.
  • Change management and steward capability building.
  • Measuring programme value and operating costs.
  • Sustaining master data after go-live.
  • Final Workshop: Develop a multi-domain master data roadmap covering domain priorities, hub styles, matching, governance workflows, migration, and roll-out phases.

Upcoming Dates

Selected date

Casablanca · 21 – 25 Dec 2026 · Classroom

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AbujaScheduled
2 – 6 Nov 2026€5,100—
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ViennaScheduled
2 – 6 Nov 2026€5,700—
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AccraScheduled
9 – 13 Nov 2026€5,100—
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AmmanScheduled
15 – 19 Nov 2026€3,100—
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AmsterdamScheduled
16 – 20 Nov 2026€5,400—
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BangkokScheduled
23 – 27 Nov 2026€6,100€5,490until 2 Nov
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BarcelonaScheduled
30 Nov – 4 Dec 2026€5,400€4,860until 9 Nov
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BeirutScheduled
6 – 10 Dec 2026€4,000€3,600until 16 Nov
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CairoScheduled
6 – 10 Dec 2026€3,300€2,970until 16 Nov
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Cape TownScheduled
14 – 18 Dec 2026€5,100€4,590until 23 Nov
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CasablancaScheduled
21 – 25 Dec 2026€4,300€3,870until 30 Nov
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DammamScheduled
27 – 31 Dec 2026€4,200€3,780until 7 Dec
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27 – 31 Dec 2026€4,400€3,960until 7 Dec
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DubaiScheduled
3 – 7 Jan 2027€4,400€3,960until 14 Dec
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ErbilScheduled
10 – 14 Jan 2027€3,100€2,790until 21 Dec
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IstanbulScheduled
11 – 15 Jan 2027€4,700€4,230until 21 Dec
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JeddahScheduled
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Kuala LumpurScheduled
25 – 29 Jan 2027€4,400€3,960until 4 Jan
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KigaliScheduled
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1 – 5 Feb 2027€5,400€4,860until 11 Jan
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LondonScheduled
8 – 12 Feb 2027€5,600€5,040until 18 Jan
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MadinahScheduled
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MadridScheduled
15 – 19 Feb 2027€5,400€4,860until 25 Jan
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ManamaScheduled
22 – 26 Feb 2027€4,700€4,230until 1 Feb
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22 – 26 Feb 2027€4,200€3,780until 1 Feb
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1 – 5 Mar 2027€5,300€4,770until 8 Feb
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OnlineScheduled
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