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13min chapter
#222 [Radar Recap] Scaling Data Quality in the Age of Generative AI
DataFramed
Challenges in Data Quality and Trust in the Age of AI
The chapter explores the persistent challenges surrounding data quality across various layers of systems, particularly in the context of generative AI products. Discussions focus on the evolving definition of data quality, the importance of trust, and the complexities of managing data sources, code, and infrastructure components. The speakers emphasize the need for continuous improvement in data quality management and detection capabilities to build reliable data systems in dynamic data ecosystems.
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