Name parsing and standardization is an important part of any data quality initiative. Unfortunately
names are not like Social Security Numbers (SSN) or phone numbers where one character difference
would mean a different entity.

IST's name parsing and name standardization SSIS component can be used to improve the data
quality of names both personal and company. Improving the data quality of names can lead to better
customer service, better data available for decision making and business intelligence which can
translate into increased revenue.

Name parsing and name standardization involve several different processes:

Name Standardization
Remove any additional non-alphanumeric data or noise information. Apply standardized rules
for titles, prefixes, suffixes etc. Standardize common business names and abbreviations.

Name Parsing
Name parsing involves splitting an input string such as: Mr. John R. Smith Jr into title or prefix,
first name, last name, middle initial, middle name and other names.

Gender Coding
The gender coding module of our name parsing and name standardization attempts to determine
the gender of the incoming name. The output options for gender coding are: M - male, F - female,
B - could be both male or female, C - company name, U - unknown. Gender coding is essentially a
data enrichment operation - appending additional information based on your existing data.

Name Conversion
As an option to the name parsing and name standardization process common nicknames can be
converted to the corresponding full name. For example:


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