Analysis / Data engineering and quality
Reconcile a dashboard metric to source records
Recalculate a dashboard metric from source records, trace variance to joins and filters, and produce reproducible evidence for definition review.
Data analyst · Analytics engineer
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Your starting prompt.
Reconcile [dashboard metric] against [source records] for [period] using the documented filters and calculation. Compare total, distinct entity count and grouped subtotals, then trace discrepancies to date boundaries, duplicated joins, exclusions or revisions. Produce a variance bridge with supporting record IDs and reproducible calculations. Do not declare one result authoritative until the business definition and source of record are agreed.
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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
Two totals can both be correct when they use different event dates, grain or filters.
This starting prompt has no published worked example yet. Begin with a small sample and check the calculations before relying on the result.
Before you begin
- 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.
Take the next step
Make it your investigation.
Copy the prompt above, create or open your Workspace, and paste it into Chat. Add the inputs you have permission to use and adapt the assumptions with your agent.
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