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We've added NameParser to our own consulting toolbox. Very
impressive guys!
Steve Clarke
Project Manager
FMS
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All in all, the results are impressive! I'd recommend using
NameParser for painless parsing.
Sean Kavanagh
ElementK Journals
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Great product, and it's performance speed is very impressive.
Chris Baylis
Data Integration Manager
Sainsbury's Supermarkets Limited
LONDON - UK
chris.baylis@sainsburys.co.uk"
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Thanks very much for your help. You have created a very nice control that is
easily implemented.
David E. Ward
Publicans Consulting
www.publicans.com
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This is an excellent utility - Thank you!!!!
David Peach
QBT Consulting
www.qbt.com.au
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We purchased NameParser back in 2005 and have been very happy
with it. It truly has worked extremely well!
Chris Lloyd
http://www.lodestonesolutions.com/
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Your utility is so useful to me. I'm a
pharmacist and I receive from the state of Mn a listing of all providers and
their name and title all in one field! There are 22,607 records.
NameParser
is a life-saver for me.
Mike McEachran R.Ph.
Hinckley Drug Pharmacist -
USA
www.hinckleydrug.com
mike@hinckleydrug.com
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NameParser is a excellent example of a utility that does a single task with
pizzazz. This COM component separates names stored in a single field into separate components
--first name, middle name, and last name -- making it the perfect tool for
fixing poorly structured tables. The program handles prefixes, suffixes, and
reverse names (such as "Smith, Margaret"); adjusts case; and even uses an
editable database of names in order to assign a likely gender to each name.
For example, if you have "Mr. Robert A. Edwards, Esq" stored in a single
field, NameParser will separate the name into new fields and add another
property indicating the name is male.
It processes around 1,000 name per second which is impressive.
NameParser can even assign a confidence rating to inform you of how accurate the
parsed data is likely to be. 5 stars out of 5!
Rose Vines
ZD Net
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One of the biggest headaches for database administrators is keeping data
clean. You probably cringe when you find that you have to integrate data
from another source because you know what to expect--improperly entered or
inconsistent data. Third-party mailing lists are often the worst offenders
of data normalization and integrity rules--you're likely to find records
missing salutations, first and last names in one field, and entry
conventions that vary from one record to the next.
If you frequently must clean and parse data, you should definitely take a
look at NameParser, a COM component available from Info Plan Software. This
utility is specifically designed to parse name information that's stored in
a single field. The component works in code to clean and value add data.
Sean Kavanagh
ElementK Journals
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