Updated June 18, 2026
AtScale’s CPO Luis Maldonado on What It Actually Takes to Make AI TrustworthyAt Snowflake Summit last week, AtScale Chief Product Officer Luis Maldonado sat down with Ravit on The Ravit Show to talk about the announcement everyone at the conference was asking about, and the deeper problem it's designed to solve. The…
Updated June 17, 2026
It’s Got to Be the Semantic Layer, BabyAtScale's Dave Mariani and Snowflake's Carl Perry on why governed semantics, not a smarter LLM, is what makes AI agents trustworthy. For years, business intelligence ran on a human workaround. When two reports disagreed about "revenue," a trained BI analyst…
Updated June 4, 2026
AtScale for Snowflake Semantic Views: Governed Metrics, Everywhere Your Business RunsExecutive Summary Snowflake Semantic Views centralize governed metric definitions inside Snowflake, but Microsoft tools like Power BI and Excel do not natively consume those definitions. AtScale for Snowflake Semantic Views XMLA Endpoint extends governed Snowflake metrics to Power BI and…
Updated June 4, 2026
Snowflake Summit 2026: Governed Semantic Views for CoCo, CoWork, Power BI, and ExcelHow Snowflake Semantic Views reach CoCo, CoWork, Power BI, and Excel without leaving the platform Executive Summary At Snowflake Summit 2026, Snowflake and AtScale introduced a new way to extend governed Snowflake Semantic Views to CoCo, CoWork, Power BI, and…
Updated June 2, 2026
Snowflake Partnered with AtScale for a Reason: Your Semantic Layer Is Too Important to SurrenderSnowflake has embedded AtScale as the only semantic layer in its platform, extending Semantic Views to Power BI and Excel, so they get the same accurate metrics your AI gets. Snowflake, whose thousands of customers include Capital One, Toyota, and…
Updated February 10, 2026
AI Governance Isn’t Theoretical Anymore: What Enterprise Leaders Are Actually AskingAI governance discussions used to center on frameworks and theoretical risk scenarios. This month’s TDWI webinar with Cal Al-Dhubaib, head of AI and data science at Further, revealed the many ways in which theory has moved to the practical. As…
Updated November 17, 2025
How a Semantic Engine Reduces AI Query Costs Without Sacrificing PerformanceReal-time AI analytics feels like the future: instant insights, natural conversation, decisions without delay. But behind the scenes, that future comes with a big catch: every AI query costs money, and those costs compound fast. Many of our customers see…
Updated October 21, 2025
Why GigaOm Recognized Universal Semantic Modeling as the Future of AI AnalyticsEnterprise teams today are juggling Power BI and Tableau, Python and R, plus a growing collection of AI copilots and agents. The problem? Every tool seems to have its own version of what "revenue per customer" actually means. You've probably…
Updated September 25, 2025
AtScale Named Leader and Fast Mover in the 2025 GigaOm Radar for Semantic LayersI’m excited to share that AtScale has once again been recognized as both a Leader and Fast Mover in the 2025 GigaOm Radar Report for Semantic Layers and Metric Stores. This marks the third consecutive year AtScale has been placed…
Updated September 10, 2025
From Queries to Agents: The Evolution of Conversational BI in the GenAI EraI’ve been building in the business intelligence (BI) space for over two decades. I’ve seen the rise of self-service BI, the transition to cloud-native analytics, and the promise of augmented insights. Each wave brought new tools, new opportunities, and plenty…
