Configure a Bad Record Exception transformation to analyze the output of a process that identifies data quality issues in records. A record that has a data quality issue that needs further review is an exception.

The Bad Record Exception transformation receives input from another transformation or from a data object in another mapping. The input to the Bad Record transformation must contain one or more quality issue ports that receive text descriptions of data quality problems. The input to the Bad Record Exception transformation can also contain a numeric record score that the transformation can use to determine the data quality of each record. Set an upper and lower score threshold in the Exception transformation to classify records as good and bad quality based on the record score. The Bad Record Exception transformation writes exceptions and associated quality issue text to a Bad Records table.

For example, an organization needs to validate customer addresses before sending out some mail to the customers. A developer creates a mapping that validates customer city, state, and ZIP code against reference tables with a Labeler transformation. The Labeler transformation validates the fields and adds a record score to each row based on the results. The Labeler transformation also adds text that describes the quality issues for each record that has an error. The Labeler transformation adds quality issue text such as

city not valid

, or

ZIP code blank

to each exception. The Bad Record Exception transformation writes customer records that need manual review to the Bad Records table. Data analysts review and correct the bad records in the Analyst tool.