Matching measures - 6.5


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Data Governance > Third-party systems > Data Quality components > Matching components
Data Quality and Preparation > Third-party systems > Data Quality components > Matching components
Design and Development > Third-party systems > Data Quality components > Matching components
To compare one attribute of two records, you can use any of the implemented matching functions, such as Exact, Levenshtein and Jaro-Winkler, or a custom matching algorithm you created.

You can also compare two records on many attributes. For two records to match, the two following conditions must hold:

  • When using the T-Swoosh algorithm, the score for each matching function in the match rule must exceed the threshold, if any specified. By default, the threshold is set to 1. This means exact match for most matching functions, excepted for Exact - ignore case and potentially any custom matching function.

  • The global score, computed as a weighted score of the different matching functions, must exceed the match threshold. The score is equal to Σ(wi × si(r1,r2)) / Σwi where wi is the confidence weight of the matching function i and si(r1,r2) is the score of the matching function i over records r1 and r2.

In this example, the score for the Levenshtein metric on the attribute country must exceed 0.7 and the global score, with a confidence weight of 1 on each of the two measures, must exceed 0.85.

This example shows the weighted average computation that yields the global score of two similar records.