Data & AI Training
Data Quality Improvement
Shifting from reactive fixes to proactive improvement by addressing issues at source.
Overview
Remediation treats symptoms; improvement addresses causes. This session focuses on Data Quality Improvement as a proactive discipline aligned to Gate 5: Improvement in the 8-Gate Framework.
Participants learn how to use Root Cause Analysis to identify upstream drivers of poor quality and how to implement changes to processes, controls and behaviours that prevent issues recurring.
Who it is for
- Data Owners and Stewards accountable for sustained quality.
- Process owners responsible for data creation and capture.
- Governance and quality leads driving improvement initiatives.
- Transformation teams embedding quality into change programmes.
What you will learn
- The difference between remediation and improvement.
- How to identify upstream causes of quality issues.
- How to design preventive controls.
- How to prioritise improvement initiatives.
- How to embed quality into processes and behaviours.
- How improvement supports long-term trust and efficiency.
Agenda
- Why quality issues recur.
- Root causes beyond “bad data”.
- Designing preventive controls and changes.
- Prioritising improvement opportunities
- Measuring the impact of improvement.
- Examples and discussion.
Delivery and format
Delivered as a 1 hour interactive virtual session. Can be extended into an improvement planning workshop
- Format: Live virtual or on site.
- Group size: Up to 25 participants recommended.
- Optional: Follow-up hands-on improvement planning workshop.
Next steps
This course is commonly paired with: DG7 · Root Cause Analysis, DQ5 · Data Quality Monitoring & Reporting and HBG4 · Measuring Success & Maturity