validácie

Validácie (validation) is the process of confirming that a product, process, system, or set of data meets defined requirements and is suitable for its intended use. It involves documenting objectives, defining acceptance criteria, designing appropriate tests or evidentiary collection, and evaluating whether results meet those criteria. Validation is distinct from verification, which checks that a product is built according to specifications; validation asks whether the right product or outcome has been built in the first place.

Applications of validácie occur across several domains. In data handling, data validation ensures input data conform to expected formats, types, ranges, and relationships to maintain data quality. In software and IT, software validation verifies that applications and their environments reliably fulfill stated requirements and perform under real-world conditions. In manufacturing and life sciences, process validation demonstrates that production processes consistently yield products meeting predefined quality standards, often through qualification activities and documented evidence.

Methods and best practices commonly used in validácie include establishing a validation plan and acceptance criteria, performing planned testing or experiments, collecting traceable evidence, and maintaining thorough documentation. Model validation in data science or statistics uses hold-out data, cross-validation, and performance metrics to assess predictive quality. Risk assessment and ongoing monitoring are frequently integrated to ensure that validity remains proven as inputs, environments, or requirements evolve.

Regulatory and standards contexts frequently drive validation activities, especially in pharmaceuticals, medical devices, and other regulated industries, where validated processes and systems are required to ensure safety, efficacy, and compliance. See also: validation (model), data validation, quality assurance.