Data Audit

The challenge

After every ETL run, someone had to manually spot-check whether the data landed correctly across multiple disconnected systems — slow, and easy to miss edge cases.

Our approach

• 1

  Built automated validation rules that run immediately after each ETL job, comparing source and destination record counts, schemas, and key fields.

• 2

  Designed a fault-line report that pinpoints exactly which stage of the pipeline introduced a discrepancy.

• 3

  Integrated alerting so failures are flagged within minutes, not discovered days later.