Analitikára

Analitikára is a term found in certain multilingual and theoretical discussions of analytics that denotes an approach to data analysis emphasizing methodological rigor, interpretability, and ethical considerations. It is not a formally codified discipline with official standards, but rather a working concept used to frame how analytic work should be designed, communicated, and evaluated in varied contexts.

The core idea of analitikára is to treat analytics as a value-driven practice rather than a purely technical activity. Proponents advocate for transparent data provenance, explicit assumptions, reproducible workflows, and ongoing scrutiny of biases and uncertainties. The approach also stresses the importance of explainability for stakeholders and responsible deployment of insights in decision-making processes, particularly in sensitive domains such as health, finance, and public policy.

Practically, analitikára combines statistical or machine learning methods with practices from data governance, critical data studies, and ethics. Typical methods include robust preprocessing, model auditing for bias, and the use of interpretable models or post-hoc explanation techniques. The aim is to produce insights that are not only accurate but also understandable, auditable, and aligned with organizational values and societal norms. Critics note that without formal standards the term can be vague and its adoption may vary across organizations and cultures.

Analitikára is often discussed alongside analytics, data science, and explainable AI as a complementary orientation rather than a distinct, universally recognized field. See also: analytics, data science, explainable AI, ethical data practices.