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  1. Preface
  2. Introduction to Accelerators
  3. Core Accelerator
  4. Data Domains Accelerator
  5. Australia/New Zealand Accelerator
  6. BCBS 239/CCAR Accelerator
  7. Brazil Accelerator
  8. Financial Services Accelerator
  9. France Accelerator
  10. Germany Accelerator
  11. India Accelerator
  12. Italy Accelerator
  13. Portugal Accelerator
  14. Spain Accelerator
  15. United Kingdom Accelerator
  16. U.S./Canada Accelerator

Accelerator Guide

Accelerator Guide

Germany Matching and Deduplication Rules

Germany Matching and Deduplication Rules

Use the matching and deduplication rules to generate match scores and identify duplicate records.
Find the matching and deduplication rules in the following repository location:
[Informatica_DQ_Content]\Rules\Matching_Deduplication
The following table describes the matching and deduplication rules in the Germany accelerator:
Name
Description
mplt_Company_Name_Match
Uses field match strategies to identify duplicate rows based on company names. The mapplet generates Soundex codes from the company name values and uses the Soundex codes as group keys.
mplt_DEU_Company_Name_and_Address_Match
Uses field match strategies to identify duplicate rows in German data based on company name and address data. The mapplet uses a combination of characters from the company name values and the postal code values to generate group keys.
mplt_DEU_Familyname_and_Address_Match
Uses field match strategies to identify duplicate rows in German data based on surname and address data. The mapplet uses a combination of characters from the surname values and the postal code values to generate group keys.
mplt_DEU_Firstname_3CharsSurname_DOB_and_Postcode_Match
Uses field match strategies to identify duplicate rows in German data based on personal names, first three characters of the family names, date of birth, and postal codes. The mapplet generates group keys from the postal code data.
mplt_DEU_Firstname_and_PID_Match
Uses field match strategies to identify duplicate rows in German data based on personal names and personal IDs grouped. The mapplet generates group keys from the personal ID data.
mplt_DEU_Firstname_Surname_2ElementsDOB_and_Postcode_Match
Uses field match strategies to identify duplicate rows in German data based on personal names, two elements of the date of birth, and postal codes. The mapplet generates group keys from the postal code data.
mplt_DEU_Firstname_Surname_DOB_and_Postcode_Match
Uses field match strategies to identify duplicate rows in German data based on personal names, date of birth, and postal codes. The mapplet generates group keys from the postal code data.
mplt_DEU_IMO_Company_Name_and_Address_Match
Uses identity match strategies to identify duplicate rows in German data based on company names and addresses. The mapplet generates group keys from the postal code data.
mplt_DEU_IMO_Familyname_and_Address_Match
Uses identity match strategies to identify duplicate rows in German data based on surnames and addresses. The mapplet generates group keys from the postal code data.
mplt_DEU_IMO_Individual_Name_and_Address_Match
Uses identity match strategies to identify duplicate rows in German data based on person names and addresses. The mapplet generates group keys from the postal code data.
mplt_DEU_IMO_Personal_Name_and_Data_Match
Uses identity match strategies to identify duplicate rows in German data based on person names and personal data. The fields in the personal data column must contain a single type of data, such as telephone number, email, or personal ID. The mapplet generates group keys from the personal data.
mplt_DEU_Individual_Name_and_Date_Match
Uses field match strategies to identify duplicate rows based on person names and date data grouped by date. The mapplet generates group keys from the date data.
mplt_DEU_Individual_Name_and_Email_Match
Uses field match strategies to identify duplicate rows in German data based on person names and email addresses. The mapplet generates group keys from the email address data.
mplt_DEU_Individual_Name_and_Phone_Match
Uses field match strategies to identify duplicate rows in German data based on person names and telephone numbers. The mapplet generates group keys from the telephone number data.
mplt_DEU_Individual_Name_and_PID_Match
Uses field match strategies to identify duplicate rows in German data based on person names and the personal IDs. The mapplet generates group keys from the personal ID data.
mplt_DEU_Individual_Name_Match
Uses field match strategies to identify duplicate rows in German data based on person names. The mapplet generates NYSIIS codes from the surname values and uses the NYSIIS code as group keys.
rule_Company_Name_MatchScore
Generates a match score based on company names.
rule_DEU_Company_Name_and_Address_MatchScore
Generates a match score based on company names and addresses.
rule_DEU_Familyname_and_Address_MatchScore
Generates a match score based on surnames and addresses.
rule_DEU_Firstname_3CharsSurname_DOB_and_Postcode_MatchScore
Generates a match score based on the first names, the first three characters of surnames, the date of birth, and the postal codes.
rule_DEU_Firstname_and_PID_MatchScore
Generates a match score based on first names and any data in the personal data column such as telephone number, email, or personal ID.
rule_DEU_Firstname_Surname_2ElementsDOB_and_Postcode_MatchScore
Generates a match score based on personal names, date of birth, and postal codes.
The input format of the date of birth is assumed to be DD/MM/YYYY.
rule_DEU_Firstname_Surname_DOB_and_Postcode_MatchScore
Generates a match score based on the surnames, date of birth, and postal codes.
rule_DEU_Individual_Name_and_Phone_MatchScore
Generates a match score based on the person names and the telephone numbers.
rule_Familyname_and_Address_MatchScore
Generates a match score based on the family names and addresses.
rule_Individual_Name_and_Date_MatchScore
Generates a match score based on person names and dates.
rule_Individual_Name_and_Email_MatchScore
Generates a match score based on person names and email addresses.
rule_Individual_Name_and_SSN_MatchScore
Generates a match score based on the firstnames and any data in the personal data column such as telephone number, email, or the SSN number.
rule_Individual_Name_MatchScore
Generates a match score based on person names.