Features Overview

• Powerful Probabilistic Data Matching

• Identification of Duplicate Records

• Data Cleansing & Standardization

• Address Cleansing

• User friendly and cost effective

• High performance - match, dedupe or clean files containing up to 4-5 million records

• French language version available

Import data from a wide range of databases

• Text Files, DBASE, FoxPro, MS Excel and MS Access

• Import data from SQL Server, Oracle and other enterprise databases^*

• UNIX text file conversion^*

• Import and clean up to to 250 files per project

• Clean up to 4-5 million records per file^*

• Export data to Access, Text File and Excel

Data Matching

• Probabilistic & deterministic data matching algorithms

• NYSIIS and SOUNDEX phonetic algorithms;

• Advanced String Comparator functions

• Use any field as a Match Variable, including but not limited to:

  ● First Name (including aliases & nick names)

  ● Family Name (including previous family names)

  ● Date of Birth

  ● Date of Death

  ● Event/ Episode Date

  ● Sex

  ● Address

  ● Zip/ Postal Code

  ● SSN

  ● Medicare Number

  ● Business or Company name

  ● Business contact name

  ● Email Address

  ● Medical Diagnoses

  ● Unique Identifier

  ● Medicare Number

  ● Up to 8 user defined fields

• User Definable Match Weights;

• Value Specific Match Weights - i.e. the family name 'Smith', which is is very common name,  receives a lower weight than 'Felligi';

• Specify Excluded Values/ Noise Data to be ignored during matching

• Phonetic Match Exclusions (ensures that special phonetic matches such as Joan/Jean or Marie/Mary etc are not matched);

• Matched Pairs Analyzer for reviewing pairs of matched records

• Clerical Review facility for manually reviewing potential matches

Identification of Duplicate Records

LinkageWiz uses powerful probabilistic data matching algorithms to identify duplicate records, utilizing common identifiers such as name, date of birth, sex, Social Security Card Number and others. You can export the duplicate records or the records that do not have any duplicates.

Example duplicate records identified:
 

Easily Identify and Correct Data Quality Problems

Identify common data quality problems using the LinkageWiz Field Analyzer and Table View screen:

Interactive search and replace function

General Data Cleansing & Standardization

• Alpha and Numeric Corrections - Changes 0’s to O’s and 1’s to I’s. This is useful for correcting numbers that have been inadvertently been entered in name fields, for example:
      R0bert ® Robert

• Business Name Standardization - standardizes business names, removing organizational noise. For example:
  Acme Motors International Pty Ltd ® ACME MOTORS

LinkageWiz also contains a large library of business name noise data which you can customize to suit your own address cleaning requirements:

• Case Conversion
    
     Upper Case -  converts the field to uppercase e.g. Smith ® SMITH
    
     Lower Case -  converts the field to lowercase e.g. Smith ® smith
    
     Proper Case - converts the field to proper case e.g. MACDONALD ® McDonald

• City & State Standardization - standardizes city & state names to standard abbreviations

• Conversion of Accented Characters
  Upper Case (Remove Accents)  - converts to uppercase and removes accented characters
      e.g. Béatrice ® BEATRICE

  Lower Case (Remove Accents) - converts to lowercase and removes accented characters
      e.g. Béatrice ® beatrice

• Digits Only function - Only permits numeric digits

• First & Last Word functions - creates a new field based on the first or last word of another field

• NYSIIS & SOUNDEX functions - creates a new field based on the NYSIIS or SOUNDEX codes of another field.

• Removal of Spaces and Unwanted punctuation
    
     Remove Embedded Spaces - e.g. 618 123456 ® 618123456
    
     Remove Invalid Punctuation - Only the characters A-Z, digits, space, single quotation
        mark or hyphen are permitted

Address Cleaning & Standardization

LinkageWiz has a powerful addressing cleaning & correction module that cleans and corrects address data. 

Email Cleaning

Clean and corrects email addresses. Separate email addresses into separate sub-component values for account, domain, sub-domain & country.

   

• Recode

Recoding allows for the replacement of specified field values with new values. Custom recoding schemes can be developed and saved for future use. For example, a recoding template could be developed to standardize school names:
 

SCH ® SCHOOL

H.S. ® HIGH SCHOOL

H S ® HIGH SCHOOL

ACAD ® ACADEMY

• Concatenate

Allows two fields to be joined together to create a new field.

• Truncate

This function allows for the truncation of the contents of an existing field. The results may be saved into the same field or optionally into a new field (recommended). Contents may be truncated a specified number of characters from either the left:

E.g. SMITH ® SMI ;

or from the right:

E.g. SMITH ® ITH

 

• Splitting of Full Name into subcomponents

Splits a full name into given name and family name components, for example:

Williamson John ® John Williamson

• Derivation of Sex

Adds missing sex information to a list by deriving sex for the first name field (based on algorithms and a library of greater than 30,000 first names).

• Merge Data Tables

Merges two tables using common key(s)

Geocoding

LinkageWiz includes a powerful geocoding engine that allows you to geocode your address data. Latitudes and Longitude coordinates can be assigned to your data using any available geographical reference file.