Skilirium

Recognises a past event judged against present data

Q-315 · Skill knobit · Activity: Derive data quality rules · Competence: Data quality

A rule about a past event checked against today's state: today's reference data, current_date, the current version of a dimension. Rows that were valid when they were recorded start failing when the world moves on, and the failure count grows without a single bad row being loaded.

Can AI do this?

People still lead Few or none of the tested AI models showed they master this. 0 of 4 models in the current benchmark master it.

ModelTierProbability of masteryStatus
gemini-4-argonFlagship 36%Not shown
gemini-3.1-pro-preview*Flagship 100%Mastered
gpt-6-astra*Flagship 100%Mastered
claude-fable-5-1*Flagship 100%Mastered
gemini-3.8-flash*Mid tier 100%Mastered
gpt-6.1-sol*Mid tier 99%Mastered
claude-sonnet-5-5*Mid tier 100%Mastered
gemini-3.5-flash-liteLow cost 14%Not shown
gpt-6-lunaLow cost 12%Not shown
claude-haiku-5-5Low cost 79%Not shown

* From the earlier benchmark of 2026-10: 10 data-modelling test tasks, 3 runs per task, graded by claude-opus-5-5. These models have not taken the current 123 tasks yet; the two methods differ, so compare their figures with care. They are left out of the “most models” counts and the best-model picks.

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 check and the as-at reading it needs

How it is assessed: Flags the deficient case and passes the acceptable one. Deficient: account_currency_code checked against today's ref_currency; after EEK was withdrawn in 2011 every account opened in kroon fails Acceptable: The check joins the ISO 4217 version valid on the account's opening date; current_date only in rules that are about now

Also known as: Judged at the wrong time (data quality rule)

Related knobits

Builds on

All 30 knobits of Derive data quality rules.

Source: Review checklist 03-dq-rules (data-quality), row 15; ISO 25012; DDL 2014; this skill (06-physical.md); formerly data-modelling K-715