Analysis / Data engineering and quality
Check join keys before combining datasets
Profile candidate join keys, measure unmatched records and row multiplication, and propose joins that preserve the intended business data grain.
Data analyst · Analytics engineer
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Your starting prompt.
Before joining [dataset A] and [dataset B], profile candidate keys for nulls, duplicates, format differences and unmatched values. Test the expected relationship and calculate row multiplication and metric changes after each proposed join. Show orphan records and ambiguous key groups. Recommend a reviewable join strategy that preserves the intended grain, without using arbitrary first matches to hide identity problems.
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Method and review
Keep the assumptions visible.
Profile keys, row counts, types, missing values and join cardinality. Retain source lineage and concrete exception records so a correction can be checked.
For this task, check
Normalizing IDs can collapse separate entities, so normalization rules require business validation.
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- Bring exports you are allowed to upload, or data your Workspace can already query.
- Choose the reporting period and agree what each record represents.
Work with permitted files or queryable data. Verify the result against the original records.
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