Maintaining data integrity in large organizations presents multiple challenges, including managing vast amounts of information across diverse systems. Inconsistencies can arise from data input errors, system migrations, or external integrations, leading to discrepancies. Ensuring compliance with regulations also complicates data management. Organizations must implement robust data quality frameworks and continuous monitoring to identify and rectify integrity issues proactively. Furthermore, enhancing employee training and employing automated tools can help mitigate risks associated with human error, improving overall data governance and reliability.