User manual BUSINESS OBJECTS DATA QUALITY MANAGEMENT SDK 4.0 DEVELOPER GUIDE 14.0.0.1

[. . . ] Developer Guide SAP BusinessObjects Data Quality Management SDK 4. 0 (14. 0. 0. 1) 2010-12-09 Copyright © 2010 SAP AG. All rights reserved. SAP, R/3, SAP NetWeaver, Duet, PartnerEdge, ByDesign, SAP Business ByDesign, and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and other countries. Business Objects and the Business Objects logo, BusinessObjects, Crystal Reports, Crystal Decisions, Web Intelligence, Xcelsius, and other Business Objects products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of Business Objects S. A. in the United States and in other countries. [. . . ] Name Order These settings are useful when the order of the family and given names in the input data is consistent. GIVEN_FAMILY_NAME_SUGGEST and FAMILY_GIVEN_NAME_SUGGEST : These values specify which rule to choose in order to break a tie when two rules have the same confidence score. Data Cleanse chooses the rule that follows the suggested name order. UNKNOWN: Data Cleanse chooses the rule with the highest confidence score based on information in the dictionary and rule file. Assign Prenames 229 2010-12-09 Data Cleanse Reference Option Description Defines how name and occupational title data found in separate input fields are associated. YES: Data Cleanse assumes that the name and title data describe the same person and is associated. NO: Data Cleanse assumes that the name and title data is not associated. For example, the diagram below shows the difference in the output based on the Associate Name Title setting. Associate Name Title Specifies whether you want to use presumptive name parsing on Name_Line input fields. Data in the Name_Line input field is treated as a name. Enable Presumptive Name Parsing NO: Turns off presumptive name parsing. Data in the Name_Line input field that does not parse as a name remains unparsed and is output to the Extra field. For example, if the data contains an automobile brand and model in a Name_Line input field, the Data Cleanse transform tries to parse the information as a name based on rules in the cleansing package. If the option is set to NO and Data Cleanse is not able to assign the data, the unparsed data is output to the Extra field. If the option is set to YES, Data Cleanse will assign the data as a name. 15. 5. 1 Gender standardization options The gender standardization options control which input fields Data Cleanse uses to assign gender. These options are found in the Gender Options group under Options > Standardization Options > Person. 230 2010-12-09 Data Cleanse Reference Note: The options in this group apply only to person and firm cleansing packages. Option Description When the gender of the prename and Given_Name1 are unassigned or ambiguous, assigns gender based on the gender of the parsed Given_Name2. Use Given Name2 To Assign Gender NO: Turns off the option. For example, if the option is set to No, the gender of the name Pat Robert Smith is ambiguous because the Given_Name1, Pat, is ambiguous. However, if the option is set to Yes, the gender is Strong_Male because the Given_Name2, Robert, is Strong_Male. The same logic applies if the name were P. Robert Smith; the Given_Name1, P, is ambiguous. When the gender of the prename, Given_Name1, and Given_Name2 are unassigned or ambiguous, assigns gender based on the gender of the family name. Uses Family_Name1 if gender is assigned and is not ambiguous. Uses Family_Name2 if unable to use Famiy_Name1. [. . . ] weighted scoring A method of comparison that provides you with a greater degree of control in the matching process. This method allows you to use contribution values to place more or less importance on various match criteria. word breaking Breaks the input line down into smaller, more usable pieces. By default, Data Cleanse breaks an input line on white space, punctuation, and alphanumeric transitions. [. . . ]