Achieve better, faster matching accuracy at lower costs. Accurate, efficient entity resolution is essential to data quality. Simplify, streamline and automate by combining machine learning with human expertise, all with less reliance on IT.
Choose columns from your data required for finding duplicates.
03. Tag records
Analyze record pairs and categorize them as match, non-match or unsure per your business use case.
04. Analyze results
Based on the selections made in previous steps, match rule and potential match keys are generated.
Put business users in control.
Present business users with data in the form they understand best. With Smart Data Quality, they can verify if the Machine Learning model is suggesting the right match decisions with just a few clicks. Download our whitepaper "Data Quality Gets Smart" to learn more.