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• Ongil Fuzzy Match version 1.0 – Direct download

To illustrate, consider a data integration job where contact details data from multiple sources have been combined. The ‘Address’ field in the integrated file could have


“TB ELECTRONICS (ENTERPRISE 1)PTE. LTD.1 KONG MO KIO ELECTRONICS PARK ROAD#01-01 TB ENGINEERING HUB567710 SINGAPORE ”
and
“TB Electronics (Enterprise 1) PTE L#01-01 TB Engineering Hub1 Kong Mo Kio Electronics Park Road56771 SINGAPORE”


in two different records. It is clear that these two entries point to the same address, but how can this be detected?
OngilSmartFuzzyMatch component will identify that these two entries are possible duplicates, and group the corresponding records under one cluster. Moreover, a similarity score will also be provided to show how similar the values are – with 1 indicating an exact match and 0 indicating no similarity. Mutliple fields can be selected to identify similar rows. For instance, in addition to the ‘address’ field, a ‘first name’ field can also be added, and OngilSmartFuzzyMatch will consider values in both fields to identify similar rows.
The results will presented in two files – “clean.xlsx” which will contain all unique records (records which have no similarity with other records), and “duplicates.xlsx” which will contain all similar/duplicate records grouped into clusters (reference by cluster_id). All records in one cluster will be similar to each other.

Ongil Fuzzy Match allows you to find duplicates in your given data by checking in multiple columns and combining the results together,thus finding duplicate rows in the data instead of just duplicate column values

Release version: 1.0.0 – 2019-08-12 06:04:43