The appropriate dimension is Reasonableness. A value may comply with technical and business-domain constraints while still being implausible in its operating context. An individual customer purchasing 750,000 office chairs is technically possible, but it is sufficiently unusual that it should trigger review.
Reasonableness controls evaluate whether values and combinations of values fall within credible expectations. These controls often depend on business context, historical behaviour, peer comparisons, statistical limits, or relationships between multiple fields.
The current DMBOK2 revision standardizes the term Reasonableness within its nine standard dimensions. The broader DMBOK2 dimension framework links reasonableness to whether data should be regarded as credible within the operational context.
Useful controls might compare order quantity against customer type, historical maximums, product availability, typical basket size, or statistical deviation from normal purchasing behaviour.
Reasonableness rules are especially valuable for identifying errors that conventional validation cannot detect. However, unusual data should not automatically be treated as incorrect; it should usually be flagged for investigation.
Reference Topics: DAMA-DMBOK2 Chapter 13 — Reasonableness; Statistical Validation; Exception Detection; Business Rules.
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