Start with a defined trigger
A data owner approves a duplicate review for a defined record type.
Scheduled duplicate check-to-review queue
This is a proposed workflow pattern. We confirm data access, permissions, integration options and review ownership with your team before implementation.
Never merge solely on a name similarity score. Protect personal information and preserve distinct legal entities.
A data owner approves a duplicate review for a defined record type.
Collect permitted identity fields, trusted identifiers, source provenance and approved matching criteria.
Suggest candidate groups with the evidence for and against a match.
A data steward verifies identity and approves any merge, including which history and relationships must survive.
Execute accepted merges through the system's supported process and retain an audit trail.
Measure false matches, missed duplicates, lost relationships and review effort.
Keep the input, relevant context, review decision and final result connected. When a reviewer corrects something, use that evidence to improve the instructions or integration, then validate the change against representative cases.
The workflow stays centered on your business. The engagement determines who learns, implements and operates it.
Learn through courses, practical training and workshops. Get feedback as you apply the lessons to your own project.
Explore courses and workshops ↗Get everything in DIY, three months of workshops, weekly team sessions and direct implementation coaching.
Explore guided implementation ↗Include all the learning and guidance, with ownership of agreed operations and major implementation decisions.
Explore managed delivery ↗Prepare a review queue for data-quality issues with clear ownership, source evidence and downstream context.
Explore this solution ↗Looking for a course, help with a difficult problem, or someone to build a solution? Tell us where you are and what you'd like to do next.