What is Data Quality? Defining Data Quality in the Age of AI

The value of data hinges on its quality, which is not solely defined by accuracy or completeness but also by ethical, legal, and contextual considerations. This article reviews the concept of data, examines the evolution of definitions of data quality (information quality), and introduces the FACT+ Framework - Fairness, Accuracy, Completeness, Timeliness, and other contextually relevant dimensions (PLUS) - as a comprehensive approach to understand and improve data quality. FACT+ provides a long-overdue update to understanding data quality to support data-driven developments, such as analytics, artificial intelligence and smart products and services.