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Tech on the Rocks
Semantic Layers: The Missing Link Between AI and Data with David Jayatillake from Cube
Feb 20, 2025
David Jayatillake, VP of AI at Cube, shares his expertise on the critical role of semantic layers in bridging raw data and actionable insights. He reveals how Cube achieved 100% accuracy in natural language data queries using semantic layers, vastly outperforming traditional methods. The conversation dives into the challenges of building these layers, emphasizing the significance of clear naming and documentation. Jayatillake also discusses future trends, including AI-powered features set to launch in 2025, and the potential of LLMs as intelligent agents.
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Quick takeaways
- Semantic layers act as a vital connector between raw data and meaningful business insights, improving the accuracy of AI-driven data queries.
- David advocates for a phased approach in implementing semantic layers, emphasizing the importance of starting with critical data points for manageable development.
Deep dives
David's Background and Semantic Layer Insights
David, VP of AI at Cube, has extensive experience in data analytics and engineering, having previously led Delphi Labs where they focused on AI interfaces for semantic layers. He discusses how traditional text-to-SQL methods often fail due to their inability to accurately understand a business's specific data models, causing inaccuracies and inconsistencies. The semantic layer, being a knowledge graph that codifies relationships among data elements, addresses this gap by providing the necessary structure and context to query data more effectively. This framework allows businesses to abstract complex data models into understandable entities, making data querying more accessible and reliable.
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