Abstract: A method and system for repairing data with incongruent or incompatible types that detects anomalies in human resources data, and if anomalies are present in the data, then suggests to a user corrections and synchronizing actions that better match patterns in the data, specifically listing reasons why the data is potentially erroneous and justifies the suggestion based on objective data to aid the user in accepting corrections and synchronizing actions or performing further review and analysis on the data using the method and system.