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DataFramed

#222 [Radar Recap] Scaling Data Quality in the Age of Generative AI

Jul 3, 2024
41:20
Snipd AI
CEO Barr Moses, Cofounder Prukalpa Sankar, and CEO George Fraser discuss scaling data quality for generative AI. Topics include challenges in data quality and trust, cultural issues, importance of data quality in AI use cases, permissions complexity in AI applications, and impact on organizational success.
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Podcast summary created with Snipd AI

Quick takeaways

  • Maintaining high-quality data is crucial for generative AI applications, necessitating improved data governance practices.
  • Establishing trust in data products requires shared context, data product score metrics, and enhanced detection capabilities.

Deep dives

The Importance of Data Quality in the Age of AI

As organizations increasingly adopt AI and machine learning technologies, the significance of maintaining high-quality data is more critical than ever. Leaders in the data business, such as Bar Moses, Prakal Pasankar, and George Frazier, discuss the challenges organizations face in ensuring data quality. Bar Moses highlights the persistent issue of data quality and the changing data environment, emphasizing the need for improved management practices. She notes that while demands on data infrastructure have evolved significantly, management of data quality remains relatively unchanged, with many data leaders still relying on manual approaches to quality assurance.

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