Data Governance & Data Quality Management
Overview
Without clear ownership, standards and quality controls, data becomes unreliable and risky. This course covers data governance frameworks, roles such as data owners and stewards, data quality management, metadata and master data, and the policies that make data trustworthy and usable.
Who should attend
Data managers, IT and business intelligence staff, data stewards, compliance officers, and business process owners.
Training methodology
Interactive presentations, practical exercises, case studies, group discussions, role-plays where relevant, and a personal action plan that participants apply in their own work.
Objectives
By the end of this course, participants will be able to:
- Explain data governance frameworks and benefits
- Define data roles, ownership and decision rights
- Assess and improve data quality
- Manage metadata, master and reference data
- Develop data policies and a governance roadmap
Course outline
Day 1Why Data Governance
- Data as an asset
- Governance frameworks
- Common data problems
- Maturity assessment
- Discussion
Day 2Roles and Ownership
- Data owners and stewards
- Governance councils
- Decision rights
- RACI for data
- Design exercise
Day 3Data Quality
- Quality dimensions
- Profiling and measuring quality
- Root causes of poor data
- Improvement processes
- Quality exercise
Day 4Metadata and Master Data
- Data catalogues and dictionaries
- Master data management
- Reference data
- Data lineage
- Case study
Day 5Policies and Roadmap
- Data policies and standards
- Data security and privacy links
- Measuring governance
- Implementation roadmap
- Action plan
