Updated January 6, 2026
Data & Analytics Predictions for 2026As 2025 comes to a close, one thing is clear: the experimentation phase of GenAI in data and analytics is ending. In its place, enterprises are entering a more pragmatic era focused on trust, governance, economics, and tangible business outcomes.…
Updated January 6, 2026
Looking Back at 2025: Rating My Predictions on AI, Semantics, and Data DemocratizationLast year, I made a set of predictions for data and analytics trends for 2025: "The Future of Data & Analytics: Trends to Look For." Now that the year has wrapped, it’s time to put those forecasts to the test…
Updated December 22, 2025
The Rise of AI Analysts and the Infrastructure They RequireI've been building analytics software for more than two decades. I've watched waves of innovation promise to democratize analytics, including self-service BI, cloud warehouses, and natural language query systems. Each wave delivered value, but also exposed new challenges. We're now…
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 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…
