Dev Tools · 1h ago
Debugging Data Pipelines: Why 18% Fewer Rows Needs a Plan
A pipeline job finishes without error but produces a table with 18% fewer rows. Before rerunning, engineers should preserve both the before and after states with durable identifiers like Delta table versions. The article outlines a methodical approach: pin down the two states, test the smallest useful explanation, and leave evidence others can challenge.
Meridian48 take
Practical advice for data engineers, but the core problem—unexpected row drops—is a common pain point that many teams handle ad hoc; this article offers a structured playbook worth adopting.
data-pipelinesdebugging