Practice lineage-driven debugging vocabulary: tracing NULLs upstream, metric drops, broken field investigation, and root cause analysis using data lineage.
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An engineer says 'we used lineage to find where the ___ came from.' What data quality issue are they debugging?
NULL values propagating through a pipeline are a classic data quality issue. Lineage lets engineers trace a NULL back through transformations to the source table or pipeline step where it was introduced.
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A metric dropped 20% overnight. The correct lineage-driven debugging step is to:
Lineage-driven debugging starts with the lineage graph: trace the affected metric back through its dependencies to find which upstream source or transformation was updated around the time the drop occurred.
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What does 'trace the broken field upstream' mean?
Tracing upstream means following the lineage graph in reverse — from the broken output field back through each transformation step — to identify the earliest point where the data was incorrect.
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'Root cause analysis using lineage' means:
In data debugging, root cause analysis using lineage means following the dependency graph backwards to find the ultimate origin of a data quality issue — not just the symptom but the actual cause.
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A colleague says: 'The lineage shows the source table was ___ at 2am — that explains the metric drop.' What word fits?
When a source table is updated (new data loaded, rows changed, or schema modified), it can cause unexpected changes in downstream metrics. Lineage timestamps help correlate source updates with downstream anomalies.