Common Data Quality Dimensions

Data quality dimensions are criteria used to evaluate how good and reliable data is. Key dimensions include accuracy (correctness of data), completeness (using all necessary information), consistency (uniformity across datasets), timeliness (being up-to-date), and validity (adherence to rules or formats). These dimensions help organizations trust their data for decision-making, ensure processes run smoothly, and reduce errors. Essentially, they ensure data is trustworthy, relevant, and usable, supporting effective business insights and operations.