Enhancing Data Quality with Generative AI

This chapter investigates the intersection of Generative AI and data quality, emphasizing the role of semantics in understanding data context. It clarifies the differences between data quality and observability tools, highlighting their unique user audiences and marketing strategies. Furthermore, the chapter discusses the challenges of unstructured data and the necessity for collaboration and a culture of accountability to maintain data quality in AI applications.