Navigating Data Quality in Generative AI

This chapter examines the complexities of assessing data quality in generative AI, highlighting the shift towards open-ended tasks and the necessity for qualitative approaches. It emphasizes the shared responsibility of data and governance teams in enhancing data quality frameworks and cultivating a proactive data culture. The discussion also underscores the importance of addressing challenges in defining data quality for unstructured data and the critical role of data management processes in maintaining data integrity.