Lookup Validation in ETL Workflows

Practical data validation articles for ETL workflows, source files, and automated data quality checks.

Advanced ETL Processor
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Lookup validation checks whether a value exists in an approved reference list or table. Advanced ETL Processor Enterprise validates lookup values inside a visual ETL workflow, rejects or routes unknown codes, logs the failure reason, and keeps the original source data unchanged. If the customer code, product code, or department code is unknown, the workflow knows before the database starts making that face.

Lookup validation in Advanced ETL Processor

Reference data keeps imports honest

Lookup validation is useful when source files contain codes that must already exist elsewhere. It prevents orphan records, bad categories, and reports grouped under values nobody recognises.

In Advanced ETL Processor, the lookup reads from a database, file, or repository object. Failed lookups are logged, rejected, or routed for correction.

Good lookup validation examples

  • Product codes must exist in the product table.
  • Customer IDs must exist before orders are loaded.
  • Country or currency codes must match approved lists.
  • Department codes must match the finance structure.

When not to reject immediately

If new reference values are expected, route them for review instead of blocking the entire file. Some workflows need a quarantine lane, not a brick wall. The data still gets controlled, and nobody has to restart the whole run because one new product appeared.

Useful references

See working with large value lists, Advanced ETL Processor benefits, and Microsoft's overview of keys and constraints.

Video

Next steps

If this validation rule belongs in a repeatable ETL process, configure it in the Validator object, test it on a sample file, then decide whether failed rows should be rejected, logged, or routed for review.

Keep the original data unchanged. Raw files are still the witness statement.