Autofilling the Boring Semantic Layer: From Sakila to Chat-BI with dltHub

Adrian Brudaru, Co-Founder & CDO, discusses the concept of the Boring Semantic Layer (BSL) and its integration with modern data tools to simplify semantic layer complexity in data engineering. Unlike traditional semantic layers trapped within specific BI tools like Looker, Tableau, or Power BI, BSL offers a pragmatic approach by being developer-friendly, Python-native, and easily integrable with existing processes without the need for extensive infrastructure. It embraces explicit, deterministic definitions, avoiding the pitfalls of complex ontologies and dynamic join path optimization that often lead to performance issues. BSL leverages the Model Context Protocol to transform the semantic layer into an API for AI, enabling natural language interfaces like "Chat-BI" to interact with data backed by reliable semantic definitions. The demo presented showcases the fusion of dlt's schema discovery, LLM inference, and BSL to automate the creation of semantic layers, allowing for consistent data consumption across various interfaces such as dashboards, APIs, and AI agents, thereby reducing manual work and enhancing data governance.