Run the failure
Use the red CTA to create the analytical problem intentionally.
Practice Lab · 02 · Data Foundations
Grain Under Pressure
Join order-level revenue to item-level rows and watch a perfectly valid SUM become wrong.
GrainOne-to-many joinsReconciliation
Case brief
Preserve one row per order while still bringing item information into the analysis.
01
Your task
Break it. Run the checks. Explain the evidence.
Predict the result
Before validating, decide what you expect row counts or metrics to do.
Run validation
Use the green CTA to reveal the checks that catch the failure.
Explain it
Say what broke in plain business language, not only SQL language.
02
Interactive case
Run this.
RUN THIS CASE ↓
Grain Under Pressure
Preserve one row per order while still bringing item information into the analysis.
Ready — run the case. GMV jumps even though no new order happened.
ordersgrain: order
1001$251002$401003$45SUM(gross_value)$110
JOIN items
joined result3 rows5 rows
1001 · item A$251001 · item B$25repeated1002 · item C$401002 · item D$40repeated1003 · item E$45SUM(gross_value)$110$175
Order grain is stable.
Order value repeated at item grain.
Diagnosis: aggregate items separately or remove the order-level measure before summing. Then reconcile back to $110.
Debrief unlocked
What should the analyst learn?
- State the target grain before joining.
- Compare row count and distinct business keys.
- Aggregate lower-grain data before attaching order-level measures.
03
Transfer
Use the same checks at work.
State the target grain before joining.
Compare row count and distinct business keys.
Aggregate lower-grain data before attaching order-level measures.