ETL Exception Handling for Invalid and Missing Records

Abstract

ETL exception handling for invalid and missing records is an important activity in data warehouse and reporting systems where source data must be checked before it is loaded into target tables. In enterprise environments, invalid or missing records may occur due to incomplete source files, incorrect data types, null mandatory fields, invalid reference values, duplicate keys, and poor source system controls. This article discusses how structured exception handling helps detect, classify, reject, correct, and reload problematic records during ETL processing. It explains the role of validation rules, reject tables, error logs, control totals, default value handling, reference checks, and correction workflows in improving data load quality. The article also highlights common challenges such as unclear error ownership, repeated invalid records, weak metadata documentation, late source corrections, and difficulty tracing rejected records back to source systems. A structured exception handling approach is presented to improve ETL reliability, reduce reporting errors, support audit readiness, and protect data integrity. The study concludes that effective exception handling improves data warehouse stability and ensures dependable enterprise reporting.