News
 Tip
of the Month: Leave the Parsing to MatchUp API
Merge/purge your files in different formats with
different names, addresses and city/state/ZIP(TM)
structures—with no importing or changing structures!
Melissa Data’s 32/64 bit MatchUp API easily creates
unique “matchcodes,” that look for any length of
data from any place, in any field. In addition to
processing 10-20 million records per hour, it can
also process up to 16 matchcodes in a single run for
quick results.
MatchUp API allows you to use many data types to
match records, but sometimes users with databases
containing different field types think they have to
split out the field data first and match them up.
However, the API will extract the necessary data for
you. For example, for a match code using ZIP Code
(TM), Last Name, Street Number, Street Name, and PO
Box….
Database1:
DTMapComponentEx(hDeduper,1,MP_ZIP9)
DTMapComponentEx(hDeduper,2,MP_LAST)
DTMapComponentEx(hDeduper,3,MP_ADDR)
Database2:
DTMapComponentEx(hDeduper,1,MP_CSZ)
DTMapComponentEx(hDeduper,2,MP_FULL)
DTMapComponentEx(hDeduper,3,MP_ADDR)
DTMapComponentEx(hDeduper,4,MP_ADDR)
MatchUp API will extract the 5-digit ZIP Code from
the 9-digit Zip Code data field (MP_ZIP9) in the
first database, and from a City, State, ZIP, data
field (MP_CSZ) in the second. The last name will be
taken from the Last Name data field (MP_LAST) in the
first database, and from the full name data field (MP_FULL)
in the second. And since the matchcode specified
above is only going to use some parts of the
address, the API extracts the Street Number, Street
Name, and the PO Box from the address line in the
first database, and from two address lines in the
second. Not only does this save the developer time
and reduce the complexity of your application, but
it allows you to take advantage of the accuracy of
MatchUp’s data parsing logic.
---Source:
Admound Chou, Assistant Manager of Data Quality
Tools at Melissa Data
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