Example use cases
Value range enforcement: A QTY_SOLD column must be between 10 and 20 for valid transactions. A Row check rule (QTY_SOLD Between 10 and 20) flags any record outside that range. If 27 of 237 records fall outside the range, the metric scores at 88.6%.
Conditional completeness by order type: Scope Select criteria to order_type = 'express' rows only, then add a Row check requiring carrier_tracking_number is not null. Only express orders are evaluated, so missing tracking numbers on standard orders don’t affect the score.
Cross-column consistency: Use a Col vs col rule to verify end_date >= start_date on every contract record. Any row where the end date precedes the start date is marked invalid.
Aggregate uniqueness enforcement: Use an Aggregate rule with No duplicates on applied to order_id to ensure no duplicate orders exist in the asset. A single duplicate is enough to trigger a Critical alert when combined with a zero-tolerance threshold.
Complex expression validation: Use an Expression rule to enforce a multi-column business constraint that can’t be expressed with a simple row check — e.g., discount_amount <= (unit_price * quantity * 0.30) to ensure no line item discount exceeds 30% of the line total.
Use Select criteria to narrow which rows the rule applies to before configuring Condition rules. A rule applied to all rows often produces noise when the business condition is only meaningful for a subset of the data.
