Top Data Engineering Mistakes and How to Prevent Them

In practice, mistakes in data engineering usually manifest as broken pipelines, mismatched data, or even entire systems failing to deliver reliable information. These issues might seem minor at first — a missed null value here, a misconfigured parame...