Matching Models determine how duplicates are detected. Matching models look for similarities within associated fields, and the output is a Match Confidence score that is an estimate of a how closely records match. There are two types of matching models within DataGroomr; Classic matching models which are useful for scenarios where exact matching is required and, Machine Learning Matching Models which harnesses the power of a proprietary artificial intelligence clustering algorithm to determine similarities within records.
Learn how to train a custom Machine Learning Matching Model by following the steps outlined in this article