Data & AI Training
Data Remediation & Cleansing
Fixing existing data issues safely and sustainably without introducing new risk.
Overview
When data quality issues are identified, organisations often rush to clean the data without fully understanding the impact. This session focuses on data remediation and cleansing as a controlled, governed activity aligned to Gate 6: Remediation.
Participants learn practical techniques for correcting data, managing risk and ensuring fixes do not compromise downstream systems or decisions. The emphasis is on transparency, traceability and repeatability.
Who it is for
- Data Owners and Stewards responsible for remediation decisions.
- Operational teams correcting data issues.
- Analysts and engineers implementing cleansing routines.
- Governance and risk teams overseeing data change.
What you will learn
- Different types of remediation and when to use them.
- How to assess the risk of data fixes.
- How to design controlled cleansing processes.
- How to document and approve remediation actions.
- How to link remediation to root cause analysis.
- Why uncontrolled fixes create long-term problems.
Agenda
- Understanding remediation vs improvement.
- Common remediation approaches and risks.
- Designing safe cleansing workflows.
- Approval, auditability and rollback.
- Linking remediation to governance and quality.
- Practical examples and discussion.
Delivery and format
Delivered as a 1 hour interactive virtual session. Can be extended into a remediation design workshop using real data issues.
- Format: Live virtual or on site.
- Group size: Up to 25 participants recommended.
- Optional: Follow-up hands-on a remediation design workshop using real data issues.
Next steps
This course is commonly paired with: DG7 · Root Cause Analysis, DQ4 · Data Quality Improvement and DQ5 · Data Quality Monitoring & Reporting