Data only creates value when it is trusted — and trust comes from disciplined governance, consistent quality control and clear accountability across its entire lifecycle, not from good intentions. This preparation course is built around that discipline, giving participants a structured path toward the Certified Data Management Professional (CDMP) credential while addressing the practical governance gaps most organisations actually struggle with.

The programme moves from the strategic value of data through governance, quality, architecture, security and lifecycle management, then closes by connecting these pieces back to business objectives. Participants finish with the working knowledge needed to operate confidently in data-driven environments and support sustainable data management across sectors.

Who Should Attend?

• Data professionals responsible for managing or governing organisational data
• IT specialists working on data architecture, integration or systems
• Business analysts and data stewards supporting reporting and data quality
• Managers overseeing data-related activities and strategy

Knowledge and Benefits

By the end of the course, participants will be able to:

• Explain the fundamental concepts and standards of professional data management
• Apply data governance structures and clarify data-related roles
• Use data quality principles to support accuracy and reliability
• Describe data lifecycle stages and their organisational impact
• Align data management practices with strategic business goals

Module 1: Data as a Strategic Asset

• Why data now sits at the centre of business decisions
• International data management standards and models
• Building consistency and control across data practices

Module 2: Governance: Policy, Roles and Accountability

• Purpose and objectives of data governance
• Policy development and decision-making authority
• Data ownership, stewardship and role coordination

Module 3: Data Quality and Metadata

• Core dimensions of data quality and how to monitor them
• Organisational risk from poor-quality data
• Metadata types and their role in documentation and clarity

Module 4: Architecture and Integration

• Logical and physical data structures
• Aligning architecture with business processes
• Data flow, interoperability and enterprise-wide access

Module 5: Security, Privacy and Compliance

• Access control and data protection principles
• Regulatory and compliance considerations
• Managing data-related risk

Module 6: Managing the Data Lifecycle

• Creation, use and maintenance stages
• Retention and archival requirements
• Controlled and secure disposal of data assets

Module 7: Aligning Data Management with Business Strategy

• Connecting governance, quality and lifecycle practices to organisational goals
• Building confidence to operate in data-driven environments
• Supporting sustainable data management initiatives across sectors