When you create a mapping that identifies bad record exceptions, you configure the mapping to write records to one or more database targets based on the quality of the data in the records.
The following figure shows an example Bad Record Exception mapping:
The mapping contains the following objects:
Data source
An Employees data source that contains the records to analyze for data quality.
Mapplet
The Bad_Records_Mapplet contains transformations that check for and add quality issues and record scores to source records. Rules are transformations that analyze the data and find the quality issues. For example, you can include a Labeler transformation to compare input data to reference tables. Depending on the results, you can configure the Labeler transformation to return quality issues as additional columns in the rows. You can configure a Decision transformation that uses IF, THEN, ELSE statements to examine the data and apply quality issues and record scores to the input data.
Exception transformation
The Exception transformation determines which records to write to the data targets including the bad records table and the issues table.
Good record table
The Exception transformation writes all good-quality records to the target_Employees table.
Bad Record table
The Exception transformation writes all bad-quality records to the target_EmployeeBadRecords table. Bad records require manual review.
Issues table
The Exception transformation writes quality issues to the target_EmployeeBadRecords_ISSUES table. When you view the bad records in the Analyst tool, the user interface links the quality issues to the bad records.
Optionally, the Exception transformation can write rejected records to a rejected records table. You must choose to create a separate output group for rejected records on the
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