Technical GlossaryData Engineering and AI Infrastructure

Feature Consistency Check

TR: Feature Tutarlılık Kontrolü

In One Line

A validation process that verifies whether training-side and serving-side feature values are produced with the same logic and definition.

Feature consistency checks are one of the core safeguards against train-serve skew. If the same feature is calculated differently in offline and online systems, model performance can silently degrade. Sample comparisons, hash validation, or definition-level matching checks may be used to detect this. In production AI systems, such checks act as a form of quality assurance.