Analysis / Data engineering and quality
Find conflicting metric definitions across teams
Compare metric grain, dates, filters and SQL across teams, recalculate a shared sample, and prepare canonical descriptions for owner approval.
Data analyst · Analytics engineer
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Your starting prompt.
Compare the definitions of [shared metrics] across [teams], examining entity grain, event date, filters, status exclusions and aggregation logic. Recalculate a bounded shared sample where permitted and show how each definition changes the result. Produce a definition difference table and proposed canonical descriptions for review. Preserve useful distinct measures under clear names; do not silently replace approved definitions.
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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
Similar metric names may intentionally describe different business questions.
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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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Make it your investigation.
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