Eye On A.I. #227 Sedarius Tekara Perrotta: The Importance of Data Quality in AI Systems
Dec 29, 2024
Sedarius Perrotta, co-founder of Shelf, delves into the pivotal role of data quality in AI systems. He reveals how unstructured data chaos can hinder AI performance and discusses innovative strategies to enhance data accuracy through real-time monitoring. Sedarius emphasizes the importance of harnessing legacy data while addressing current challenges in knowledge management. The conversation also touches on the future of data management in the age of generative AI and how organizations can unlock the full potential of their unstructured data for enhanced productivity and innovation.
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Knowledge Management Journey
- Sedarius Perrotta's journey began with knowledge management at a Transylvanian think tank during his Peace Corps service.
- This led to consulting for institutions like Harvard, MIT, Stanford, and the World Bank, focusing on intellectual capital.
Data Quality in Knowledge Management
- Knowledge management struggles with inherent data quality issues, including multiple versions, varied locations, and outdated information.
- Lack of transparency exacerbates these challenges, making it difficult to determine the reliability of data.
SharePoint and Data Challenges
- Sedarius Perrotta's consulting firm, Neuron Global, specialized in SharePoint, encountering firsthand the platform's data quality challenges.
- Initial enthusiasm for projects waned as data became outdated and unreliable, hindering adoption and creating a negative feedback loop.