Simple VSR algorithm - Cloud - 8.0

Data matching with Talend tools

Version
Cloud
8.0
Language
English
Product
Talend Big Data Platform
Talend Data Fabric
Talend Data Management Platform
Talend Data Services Platform
Talend MDM Platform
Talend Real-Time Big Data Platform
Module
Talend Studio
Content
Data Governance > Third-party systems > Data Quality components > Matching components > Continuous matching components
Data Governance > Third-party systems > Data Quality components > Matching components > Data matching components
Data Governance > Third-party systems > Data Quality components > Matching components > Fuzzy matching components
Data Governance > Third-party systems > Data Quality components > Matching components > Matching with machine learning components
Data Quality and Preparation > Third-party systems > Data Quality components > Matching components > Continuous matching components
Data Quality and Preparation > Third-party systems > Data Quality components > Matching components > Data matching components
Data Quality and Preparation > Third-party systems > Data Quality components > Matching components > Fuzzy matching components
Data Quality and Preparation > Third-party systems > Data Quality components > Matching components > Matching with machine learning components
Design and Development > Third-party systems > Data Quality components > Matching components > Continuous matching components
Design and Development > Third-party systems > Data Quality components > Matching components > Data matching components
Design and Development > Third-party systems > Data Quality components > Matching components > Fuzzy matching components
Design and Development > Third-party systems > Data Quality components > Matching components > Matching with machine learning components
Last publication date
2024-02-06

This scenario applies only to Talend Data Management Platform, Talend Big Data Platform, Talend Real-Time Big Data Platform, Talend MDM Platform, Talend Data Services Platform, Talend MDM Platform and Talend Data Fabric.

This scenario describes a basic Job that compares columns in the input file using the Jaro-Winkler matching method on the lname and fname column and the q-grams matching method on the address1 column. It then groups the output records in output flows:
  • Uniques: lists the records which group size (minimal distance computed in the record) is equal to 1.

  • Matches: lists the records which group score (minimal distance computed in the record) is greater than or equal to the threshold you define in the Confident match threshold field.

  • Suspects: lists the records which group score (minimal distance computed in the record) is less than the threshold you define in the Confident match threshold field.