UA Ledger · Measurement Lab · draft for review

Spot a repeated revenue total after a one-to-many join

Synthetic teaching inputs. No real campaign results or industry defaults. Change the values to inspect the model. Calculations run locally; this page sends no data and does not retain inputs after closing.

Define the intended output grain, such as one row per transaction, before joining campaign or item metadata. Count joined rows against distinct transaction keys and inspect whether each purchase amount repeats. This worksheet assumes every transaction repeats the same number of times solely to illustrate the error. A real query needs transaction-level analysis when fan-out varies.

Calculated outputs

Assumption sensitivity

Only fanout varies; all other inputs are held constant. This is not a probability range.

Equations

• Correct revenue at transaction grain: transactions*value
• Repeated joined revenue: transactions*value*fanout
• Overstatement: transactions*value*(fanout-1)

Additional constraints: true. The field minimums also apply.

Limits

Never deduplicate revenue by amount alone: different legitimate transactions can share a price. Validate keys, join cardinality and aggregation order against a small inspected sample before trusting a repaired query.

Google Analytics BigQuery Export schema · primary documentation checked 19 September 2026.