Poor data quality costs organizations an average of $12.9 million annually, making data integrity crucial for confident decision-making. With the global data volume projected to reach 175 zettabytes by 2025, managing this data effectively is becoming increasingly difficult. Continuous validation through a modern, automated approach ensures data quality at every stage of its lifecycle, providing real-time monitoring and feedback to maintain high data quality assurance processes. Automated tools such as real-time validation, continuous monitoring, and feedback loops are essential for maintaining data integrity at scale.