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7min chapter
#222 [Radar Recap] Scaling Data Quality in the Age of Generative AI
DataFramed
Challenges and Importance of Data Quality in Generative AI Use Cases
The chapter explores the pressure on data leaders to execute generative AI use cases, the significance of high-quality proprietary data in achieving competitive advantage, and the importance of data quality and governance over creating unique models. It also emphasizes the potential of AI technologies in handling unstructured data and highlights the necessity of business terms, semantic context, and trust in data output for organizations adopting data-driven decision-making.
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