I recently connected with a data engineering manager leading engineering efforts at an energy analytics company. His team processes complex data from hundreds of public sources, each with its own format, errors, and quirks. During our conversation about data quality challenges, he shared an insight that resonated deeply: This principle applies directly to QA. Every day, we generate test results that teams rely on for critical decisions.