When using the Integration project, the configure page allows for matching records from the source system to the target system to identify if records exist in the target system using different matching methods.
There are 8 match method types:
- Exact match: match records exactly (e.g. Smith matches to Smith)
Fuzzy match: the Levenshtein Distance Algorithm is used, with a maximum of 2 edits and a minimum of 3 characters, meaning that any string of 2 or fewer characters will not be used for fuzzy matching. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. For example, the Levenshtein distance between "kitten" and "sitting" is 3, since the following three edits change one into the other, and there is no way to do it with fewer than three edits:
-
kitten → sitten (substitution of "s" for "k")
sitten → sittin (substitution of "i" for "e")
sittin → sitting (insertion of "g" at the end)- Source value contains target value: (e.g. source value = Smithe matches to target value = Smith)
- Target value contains source value: (e.g. target value = Smith matches to source value = Smithe)
- Source value begins with target value: (e.g. source value = asmith@abc.com matches to target value = asmith)
- Target value begins with source value: (e.g. target value = asmith@xyz.com matches to source value = asmith)
- Source value ends with target value: (e.g. source value = andrew.smith@abc.com matches to target value = abc.com)
- Target value ends with source value: (e.g. target value = andrew.smith@abc.com matches to source value = abc.com