Semantic Layers are the missing piece for AI-Enabled Analytics

Since the introduction of ChatGPT in early 2023, Large Language Models (LLMs) have sparked interest across various industries, leading companies like Cube to explore the integration of semantic layers into applications that utilize natural language processing for data retrieval and analysis. This exploration is motivated by the idea that semantic layers, which provide contextual and constrained interfaces for LLMs, enhance the accuracy of responses in comparison to simpler text-to-SQL methods. Cube, alongside partners such as Patterson Consulting and Delphi Labs, has been working on AI-enabled analytics experiences, demonstrating that semantic layers can improve LLM accuracy. A significant study by data.world researchers has shown that incorporating knowledge graphs, akin to semantic layers, into the question-answering process of LLMs yields more accurate results. Delphi, using Cube's semantic layer, achieved a 100% accuracy rate in benchmarking tests against data.world's methodology, underscoring the efficacy of semantic layers in improving LLM performance. Encouraged by these findings, Cube has made its methodology and resources publicly available to foster community engagement and further validation of their approach.

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