About the Session
This session explores the evolution of semantic layers from the 1990s to their pivotal role in modern data management, illustrating their significance in ensuring data consistency across diverse tools. Artyom then shifts focus to the transformative impact of LLMs, particularly in understanding organizational data. He proposes a visionary model where AI, equipped with semantic layers, can access and interpret data more meaningfully, leading to natural language access, advanced cataloging, and enhanced data observability and governance. Artem encourages experimentation with Cube and other open-source technologies, fostering a community-driven approach to exploring the potential of semantic layers in augmenting AI capabilities.
