Updated December 15, 2025
Universal Semantic Layer and AI Agents: What Enterprises Need to KnowHow can enterprises prepare for a world where AI agents, not just humans, are analyzing data and making recommendations? Every data and analytics leader is grappling with this question, and the answer lies in a universal semantic layer. In my…
Updated December 10, 2025
AI Without Semantics Is a Costly Risk: Key Takeaways from EDM Association WebinarHow do you move from experimental AI pilots to production systems you can trust? That was the central question Kyle Morton and I discussed on last month’s EDM Association webinar. The data management community is keenly aware of what’s at…
Updated December 9, 2025
From Governance to Guidance: The Next Phase of AI ReadinessAI Adoption Has Outpaced AI Readiness Every enterprise I talk to right now is chasing the same goal: operationalizing AI agents and agentic analytics. The enthusiasm is there. The budgets are there. The pilots are running. But the confidence? That's…
Updated December 2, 2025
The State of the Semantic Layer: 2025 in ReviewI've been building data systems long enough to recognize when an architectural shift is real versus when it's just market noise. 2025 was the year semantics moved from "nice-to-have" to "foundational infrastructure." This wasn't driven by vendor messaging or analyst…
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 November 12, 2025
Why 57% of Data Leaders Are About to Make a Costly Mistake (And How to Avoid It)Here's a wake-up call that should concern every data leader: while 50% of enterprises have invested in semantic layers, 57% of those using vendor-native implementations are already considering platform changes this year, according to Hex's State of Data Teams report.…
Updated November 10, 2025
How AI is Transforming Semantic Modeling (and Why It Matters for the Next Generation of Analytics)Semantic modeling has always been one of the most complex parts of analytics and arguably the most important. It’s the layer where your business defines itself: revenue, margin, customer lifetime value, churn, all of these live in your semantic model.…
Updated November 3, 2025
The Golden Age of the Semantic Layer: Why AI Can’t Work Without ContextFor years, the semantic layer quietly sat behind the scenes of enterprise data systems, translating complex data models into the business logic that made them meaningful. It was a critical component for BI teams but was rarely viewed as a…
Updated October 23, 2025
ETL vs. ELT: Differences, Pros, Cons, and How to ChooseData loading seems simple on the surface — move information from here to there. The complexity emerges when you ask: at what stage should transformation occur? Before you load? After? This sequencing question, whether to restructure and clean data pre-load…
Updated October 21, 2025
7 Modern Data Architecture PrinciplesModern data architecture serves as the blueprint for scalable, AI-ready, governed analytics that empower organizations to effectively harness their data assets. For executives, data leaders, engineers, and governance teams, understanding these foundational principles is critical for building systems that deliver…
