Data & AI Training
Root Cause Analysis
Moving beyond symptoms to fix the real causes of data problems at source.
Overview
Fixing data issues without understanding their root causes leads to repeated effort, mounting technical debt and declining trust. This session focuses on Root Cause Analysis (RCA) as a core governance and quality capability.
Participants learn practical RCA techniques and how to apply them collaboratively across business, process and technology. The emphasis is on learning and improvement, not fault-finding.
Who it is for
- Data Owners and Stewards accountable for recurring issues.
- Operational and process leaders involved in data creation.
- Quality and governance leads driving improvement initiatives.
- Delivery teams responsible for upstream fixes.
What you will learn
- Why root cause analysis is essential for sustainable quality.
- Common causes of data issues beyond “bad data”.
- Practical RCA techniques suitable for data problems.
- How to facilitate RCA workshops effectively.
- How RCA feeds Gate 5: Improvement and Gate 6: Remediation.
- How to turn findings into actionable change.
Agenda
- Symptoms vs root causes in data quality.
- Typical root causes: process, behaviour, incentives, systems.
- RCA techniques: 5 Whys, cause-effect, process walkthroughs.
- Facilitating effective RCA sessions.
- Turning RCA into improvement actions.
- Examples and discussion.
Delivery and format
Delivered as a 1 hour interactive virtual session. Can be extended into a design workshop to define issue categories, workflows and ownership.
- Format: Live virtual or on site.
- Group size: Up to 25 participants recommended.
- Optional: Follow-up hands-on RCA workshop.
Next steps
This course is commonly paired with: DQ4 · Data Quality Management, DQ5 · Data Quality Monitoring & Reporting and HBG4 · Measuring Success & Maturity