Skilirium

Recognises a derived or copied column without a check

K-704 · Skill knobit · Activity: Derive data quality rules · Competence: Data modelling

A column carrying derivation — a stored total, a copied name, a path string — with no check comparing it with a fresh computation. The update anomaly was accepted on purpose; the check is what makes it safe. A snapshot meant to keep the value as it was is not a copy and needs no check: say so in the derivation.

Can AI do this?

AI does this well Most of the tested AI models master this. 8 of 10 models master it.

ModelTierProbability of masteryStatus
gemini-4-argonFlagship 99%Mastered
gemini-3.1-pro-previewFlagship 98%Mastered
gpt-6-astraFlagship 99%Mastered
claude-fable-5-1Flagship 99%Mastered
gemini-3.8-flashMid tier 99%Mastered
gpt-6.1-solMid tier 99%Mastered
claude-sonnet-5-5Mid tier 100%Mastered
gemini-3.5-flash-liteLow cost 50%Not shown
gpt-6-lunaLow cost 66%Not shown
claude-haiku-5-5Low cost 99%Mastered

Mastered means a probability of at least 90% that the model has this knobit, estimated from its graded answers. “Not shown” means the answers do not settle it either way. How the models are tested.

What it looks like in practice

Expected result: The column and its recomputation check

How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: account.holder_name copied from party.name with derivation: "copied by ETL"; the ETL step is disabled in a refactor and nobody notices for a year Acceptable: DQ-021, dimension: consistency, scope: set, comparing account.holder_name with party.name through holder_party_id, backs: [PE-057] (DQR-019)

Also known as: Derived or copied column nobody watches (data quality rule)

Related knobits

Builds on

All 31 knobits of Derive data quality rules.

Source: Review checklist 07-dq-rules, row 4; Kimball & Caserta 2004; this skill (06-physical.md)