Selecting the best-of-breed data from a group of duplicates to create a survivor

Deduplication

author
Talend Documentation Team
EnrichVersion
6.5
EnrichProdName
Talend Big Data Platform
Talend Big Data
Talend Open Studio for Big Data
Talend Data Management Platform
Talend Real-Time Big Data Platform
Talend Data Integration
Talend ESB
Talend Data Services Platform
Talend Open Studio for Data Integration
Talend Open Studio for ESB
Talend MDM Platform
Talend Data Fabric
Talend Open Studio for MDM
task
Design and Development > Third-party systems > Data Quality components > Deduplication components
Data Governance > Third-party systems > Data Quality components > Deduplication components
Data Quality and Preparation > Third-party systems > Data Quality components > Deduplication components
EnrichPlatform
Talend Studio

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

For more technologies supported by Talend, see Talend components.

The Job in this scenario groups the duplicate data and create one single representation of these duplicates. This representation is the "survivor" at the end of the selection process and you can use this survivor, for example, to create a master copy of data for MDM.

The components used in this Job are:

  • tFixedFlowInput: it provides the input data to be processed by this Job. In the real-world use case, you may use another input component of interest to replace tFixedFlowInput for providing the required data.

  • tMatchGroup: it groups the duplicates of the input data and gives each group the information about its group ID and group size. The technical names of the information are GID and GRP_SIZE respectively and they are required by tRuleSurvivorship.

  • tRuleSurvivorship: it creates the user-defined survivor validation flow to select the best-of-breed data that composes the single representation of each duplicates group.

  • tFilterColumns: it rules out the technical columns and outputs the columns that carry the actual information of interest.

  • tLogRow: it presents the result of the Job execution.