Data Quality Dimensions

Data quality dimensions are standards used to evaluate how reliable and useful data is. Key dimensions include accuracy (how correct the data is), completeness (if all necessary information is present), consistency (uniformity across datasets), timeliness (how current the data is), and validity (adherence to rules or formats). These factors help ensure data can be trusted for decision-making. Good data quality means data is accurate, complete, consistent, timely, and valid, leading to better insights and more confident business choices.