In data-rich organizations, capturing and maintaining critical data context is challenging. As data usage and model complexity grow, locating the right dataset can become slow, leading to bottlenecks.
Select Star, a data discovery and metadata platform, automatically updates a knowledge graph of an organization’s data by analyzing its structure and usage. It provides context such as popularity, lineage, and semantic models, simplifying data discovery and trust for AI and teams. These enriched metadata layers also enhance large language models, greatly improving SQL query accuracy.
Shinji Kim, the founder and CEO of Select Star, discusses metadata curation challenges, data context management, SQL generation using LLMs, and trends in metadata management with Sean Falconer in a podcast episode.
Full Disclosure: This episode is sponsored by Select Star.
Sean Falconer, an academic, startup founder, and former Googler, has published works on AI to quantum computing. He is currently an AI Entrepreneur in Residence at Confluent, focusing on AI strategy and thought leadership. Connect with Sean on LinkedIn.
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Sponsorship inquiries: [email protected]