Data Quality is often overlooked by organisations as tomorrow’s problems.
The course, illustrated with real case studies covers:
- What is Data Quality vs Data Quality Management and why does it matter?
- The Data Quality Reference Model, including architecture and processes
- Diagnosing Quality problems
- Writing business case studies and exercises
- Getting started and sustaining initiative
- The DAMA dimensions of Data Quality, plus alternative views on Data Quality dimensions
- The relationship between Data Quality, Data Governance and the other Information Disciples
- Starting and sustaining a Data Quality initiative: steps for achieving Data Quality
- The roles, responsibilities and activities involved in establishing successful Data Quality.