Data Governance and Data Quality Management
Target audience
Data and digital transformation managers, quality and IT teams, and data owners across departments.
The problem it addresses
Unreliable data causes analytics and AI projects to fail before they begin. Without defined roles, responsibilities and standards, every department handles data its own way.
Learning outcomes
- Understand data governance frameworks and their core components.
- Define data ownership and stewardship roles and responsibilities.
- Manage metadata and build a data catalog.
- Measure data quality and resolve quality issues.
- Prepare an initial plan for implementing data governance in your organization.
Daily topics
- Day 1Data governance concepts and reference frameworks.
- Day 2Roles, responsibilities, policies and standards.
- Day 3Metadata and the data catalog.
- Day 4Data quality: dimensions, measurement and remediation.
- Day 5The organizational roadmap, and how governance supports AI projects.
We recommend delivering this program in the Barcelona field format, with visits to technology facilities subject to availability.
Is this program right for your organization?
Send us your request, and we will send you a proposal covering content, format and duration.