Master Data Management and Data Quality

Course Category : Data Management

An integrated approach to governing master data and improving its quality to strengthen information reliability, reduce risk, and support decisions based on accurate and consistent data.
Duration: 5 Days
Level: Intermediate to Advanced

Introduction

Reliable data is a fundamental requirement for sustainable operations and effective risk management. Errors, duplication, inconsistency, and incomplete master records can directly affect reporting, decision-making, compliance, and operational controls. As organisations increasingly operate across interconnected systems and information sources, Master Data Management becomes an enterprise governance requirement rather than a purely technical function.
This course addresses master data principles, ownership and governance structures, data quality standards, issue analysis, record lifecycle management, and quality monitoring practices that support information integrity and organisational resilience..

Targeted Audience

Data Management and Data Governance Managers
Master Data and Data Quality Professionals
Data and Business Analysts
Risk, Compliance, and Internal Control Professionals
Information Security and Data Protection Professionals
IT and Enterprise Systems Managers
Database and Information Management Professionals
Operations and Digital Transformation Managers

Targeted Skills

Enterprise Master Data Management
Data Ownership and Accountability Design
Data Quality Dimensions and Standards
Root-Cause Analysis of Data Issues
Data Validation, Cleansing, and Standardisation
Master Data Lifecycle Management
Data Quality Metrics and Monitoring
Integration of Data Quality with Enterprise Risk and Controls

Expected Outcomes

Explain the enterprise role of Master Data Management and its relationship with data governance.
Identify domains and records that should be managed as master data.
Establish clear data ownership and stewardship responsibilities.
Assess data quality using measurable dimensions and standards.
Identify sources of errors, duplication, and inconsistency.
Define appropriate validation, cleansing, and standardisation rules.
Develop metrics for monitoring and reporting data quality.
Integrate data management with risk, compliance, and organisational resilience.

Training Topics Index

Master data concepts and distinction from reference and transactional data
Core master data domains customers, suppliers, products, assets, and employees
Master record lifecycle from creation to archival
Challenges arising from multiple systems, sources, and duplicate records
Relationship between Master Data Management and enterprise data governance

Data governance models and the roles of data owners and data stewards
Accountability, authority, and approval structures
Policies for master data creation, modification, and retirement
Standards, definitions, and data dictionaries
Access controls, accountability, and change traceability

Data quality dimensions accuracy, completeness, consistency, validity, timeliness, and uniqueness
Quality requirements based on data criticality and risk
Validation rules and data quality controls
Quality KPIs, scoring approaches, and acceptance thresholds
Data quality reporting and monitoring dashboards

Identification of errors, duplicates, missing values, and inconsistencies
Root-cause analysis of data quality problems
Data cleansing, standardisation, matching, and deduplication
Exception management, issue resolution, and escalation
Impact of poor data quality on risk, compliance, and operational continuity

Sustainable Master Data Management operating models
Continuous monitoring and systematic quality improvement
Embedding data quality controls into enterprise processes and systems
Maturity indicators and management reporting
Developing a roadmap for data management and information resilience

Course Features

Updated and Interactive Content
Hypothetical Examples and Case Studies
Pre- and Post-assessments to Measure Impact
Verified Certificate with a QR Verification Code

Master Data Management and Data Quality