Data reliability is an essential aspect of data quality that ensures trust in data for operational and decision-making purposes. Unreliable data can lead to costly mistakes, while reliable data provides a competitive edge. Common examples of unreliable data include incomplete, inconsistent, or missing data. To measure data reliability, metrics such as completeness rate, consistency rate, and accuracy rate can be used. Ensuring data reliability involves establishing data quality policies, utilizing anomaly detection, and choosing accessible data tools. By understanding and maintaining data reliability, businesses can make better decisions based on accurate and consistent data.