1. Configure scoring models on the Scores page. Scores let you assess asset risk, health, and opportunity using weighted factors and criteria. Create a scoring model, assign factor weightings, and apply it across your asset base. Each score tracks how many assets it covers and when it was last updated. Disable or re-enable scores as your evaluation needs change; disabled scores stop calculating during scheduled batch jobs but remain available for reactivation.

2. Define matching rules in Data Foundry. Matching rules identify duplicate records and enforce data consistency across objects entering PTC Orbit. Specify which fields to compare, the matching logic to apply, and whether duplicates require manual review before resolution. Activate, deactivate, or update rules as your data sources evolve.

3. Review flagged records on the Matching Data Review page. Records that fail matching rule validation surface here for manual inspection. Evaluate each flagged record, decide whether to merge, keep, or discard the duplicate, and sync clean data to production. This closes the data quality loop: only verified records enter your operational environment.