Data-Driven Podcast · 2025-12-16 · 34 min
Large Language Models (LLMs) are transforming analytics, but only when paired with the right foundation. In this episode, AtScale’s CTO and co-founder Dave Mariani, co-founder Dianne Wood, and product director Petar Staykov show how Model Context Protocol (MCP) and the semantic layer unlock trusted, governed, enterprise-ready AI. You’ll get a full end-to-end walkthrough of Claude using AtScale’s MCP server to: Discover available semantic models via list-models tools Understand metrics, attributes, and dimensional context using describe-model Run fully governed analytical queries, without writing SQL, through run-query Generate insights, summarize trends, and even build dashboards autonomously Learn why LLMs struggle without structured business logic and how semantic layers eliminate hallucinations and governance drift. You’ll also learn how AI will soon help build semantic models, not just query them - enabling faster metric definitions, autonomous metadata generation, and an “army of agents” that maintain semantic consistency as businesses evolve.
30 Hours to 90 Seconds: Blue Yonder’s Semantic Layer for Trusted Enterprise AI66 / 100Semantic Layers, OSI & AI: Why Context Beats Data AccessAI Needs Context: Semantic Layers, Metadata & Trust in 2026The AI Frontier: Semantic Layers for Autonomous Agents with Jens KröhnertComposable Analytics & the Future of the Semantic Layer: Building for the Age of AI Agents