Formalizing Personal Names

This dataflow template demonstrates how to take personal name data (for example "John P. Smith"), identify common nicknames of the same name, and create a standard version of the name that can then be used to consolidate redundant records. It also show how you can add Title of Respect data based on Gender data.

Business Scenario

You work for a non-profit organization that wants to send out invitations for a gala event. Your input data include name data as full names and you want to parse the name data into First, Middle, and Last name fields and add a Title of Respect field to make your invitations more formal. You also want to replace any nicknames in your name data to use a more formal variant of the name.

The following dataflow provides a solution to the business scenario:

This dataflow template is available in Enterprise Designer. Go to File > New > Dataflow > From template and select StandardizePersonalNames. This dataflow requires the Data Normalization Module and the Universal Name Module.

For each data row in the input file, this data flow will do the following:

Read from File

This stage identifies the file name, location, and layout of the file that contains the names you want to parse. The file contains both male and female names.

Name Parser

In this template, the Name Parser stage is named Parse Personal Name. Parse Personal Name stage examines name fields and compares them to name data stored in the Spectrumâ„¢ Technology Platform name database files. Based on the comparison, it parses the name data into First, Middle, and Last name fields, assigns an entity type, and a gender to each name. It also uses pattern recognition in addition to the name data.

In this template the Parse Personal Name stage is configured as follows.

  • Parse personal names is selected and Parse business names is cleared. When you select these options, first names are evaluated for gender, order, and punctuation and no evaluation of business names is performed.
  • Gender Determination Source is set to default. For most cases, Default is the best setting for gender determination because it covers a wide variety of names. However, if you are processing names from a specific culture, select that culture. Selecting a specific culture helps ensure that the proper gender is assigned to the names. For example, if you leave Default selected, then the name Jean will be identified as a female name. However, if you select French, it will be identified as a male name.
  • Order is set to natural. The name fields are ordered by Title, First Name, Middle Name, Last Name, and Suffix.
  • Retain periods is cleared. Any punctuation in the name data is not retained.


In this template, the Transformer stage is named Assign Titles. Assign Titles stage uses a custom script to search each row in the data stream output by the Parse Personal Name stage and assign a TitleOfRespect value based on the GenderCode value.

The custom script is:

if (row.get('TitleOfRespect') == '')
	if (row.get('GenderCode') == 'M')
		row.set('TitleOfRespect', 'Mr')
	if (row.get('GenderCode') == 'F')
		row.set('TitleOfRespect', 'Ms') 

Every time the Assign Titles stage encounters M in the GenderCode field it sets the value for TitleOfRespect as Mr. Every time the Assign Titles stages encounters F in the GenderCode field it sets the value of TitleOfRespect as Ms.


In this template, the Standardization stage is named Standardize Nicknames. Standardize Nickname stage looks up first names in the Nicknames.xml database and replaces any nicknames with the more regular form of the name. For example, the name Tommy is replaced with Thomas.

Write to File

The template contains one Write to File stage. In addition to the input fields, the output file contains the TitleOfRespect, FirstName, MiddleName, LastName, EntityType, GenderCode, and GenderDeterminationSource fields.