Configuration Guide

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Match Process

Before records in a base object can be consolidated,

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must determine which records are likely duplicates, that is matches, of each other.

The match process uses match rules to perform the following tasks:

Identify which records in the base object are likely duplicates (identical or similar)

Determine which records are sufficiently similar to be consolidated automatically, and which records should be reviewed manually by a data steward prior to consolidation

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, the match process provides you with two main ways in which to compare records and determine duplicates:

Fuzzy matching is the most common means used in

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to match records in base objects. Fuzzy matching looks for sufficient points of similarity between records and makes probabilistic match determinations that consider likely variations in data patterns, such as misspellings, transpositions, the combining or splitting of words, omissions, truncation, phonetic variations, and so on.

Exact matching is less commonly-used because it matches records with identical values in the match column(s). An exact strategy is faster, but an exact match might miss some matches if the data is imperfect.

The best option to choose depends on the characteristics of the data, your knowledge of the data, and your particular match and consolidation requirements.

During the match process,

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compares records in the base object for points of similarity. If the match process finds sufficient points of similarity (identical or similar matches) between two records, indicating that the two records probably are duplicates of each other, then the match process:

populates a match table with ROWID_OBJECT references to matched record pairs, along with the match rule that identified the match, and whether the matched records qualify for automatic consolidation.