Data-Driven Podcast

AtScale

The Data-Driven AtScale Podcast is designed to explore the impact of making smarter data-driven decisions at scale with foremost Data / AI / BI thought leaders and top technologists.Here you will find a collection of practical advice and candid conversations with industry innovators, covering technology trends, lessons learned, organizational transformation experiences, best use cases, career advice, and much more. You can find and watch all of our episodes from this page. Be sure to subscribe.

  1. ٢٨ يناير

    AI Needs Context: Semantic Layers, Metadata & Trust in 2026

    In this episode of the AtScale Data-Driven Podcast, Dave Mariani sits down with Juan Sequeda, Principal Researcher at ServiceNow and former Head of the AI Lab at data.world, to explore what’s next for analytics, AI, and trust in 2026. As AI becomes embedded across the enterprise, one issue is emerging as a hard blocker: lack of context. Large Language Models are powerful, but without semantic layers, governed metadata, and shared business definitions, they struggle to produce reliable, explainable answers. Juan and Dave discuss why metadata is no longer “documentation,” but operational infrastructure, and how semantic layers are becoming the foundation for trusted AI systems. They break down why dashboards alone can’t deliver prescriptive analytics, how AI agents are shifting analytics from insights to action, and why enterprises are consolidating around platforms that can govern context at scale. The conversation also covers: Why AI and LLMs fail without semantic contextThe rise of semantic layers as enterprise AI infrastructureHow metadata, knowledge graphs, and governance convergeWhat AI means for dashboards, agents, and analytics workflowsThe future of tech jobs, systems thinking, and human skillsIf you’re a data leader, analytics architect, or AI practitioner trying to understand how to make AI trustworthy in production, this episode explains why semantics, not models, are the real bottleneck. 🔗 Learn more about AtScale’s semantic layer and Model Context Protocol (MCP): https://www.atscale.com 🔔 Subscribe for more conversations on AI, analytics, and data infrastructure.

    ٣٣ من الدقائق
  2. ١٦‏/١٢‏/٢٠٢٥

    How MCP + Semantic Layers Turn LLMs Into Trusted BI Analysts

    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-queryGenerate 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.  Key topics in this episode: • Why MCP is the JDBC-moment for LLMs • How semantic layers make AI deterministic, trustworthy, and governed • Real demos of LLM insights far beyond simple Q&A • Automating semantic model creation using agents and SML • The future: AI copilots for BI, analytics, and semantic modeling

    ٣٤ من الدقائق

حول

The Data-Driven AtScale Podcast is designed to explore the impact of making smarter data-driven decisions at scale with foremost Data / AI / BI thought leaders and top technologists.Here you will find a collection of practical advice and candid conversations with industry innovators, covering technology trends, lessons learned, organizational transformation experiences, best use cases, career advice, and much more. You can find and watch all of our episodes from this page. Be sure to subscribe.