Blog:
Bridging AI and BI

Updated January 6, 2026

Last 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 18, 2025

This isn’t about funding. It’s about control. After 15 years helping enterprises modernize analytics, I’ve learned to ignore the size of the check. What matters is why it was written. Snowflake Ventures led AtScale’s largest equity financing to date. But…

Updated December 18, 2025

I've spent more than two decades watching the data industry cycle through architectural shifts. Each wave promised to solve this fundamental challenge: delivering consistent, governed analytics that actually scale with the business. Most failed because they optimized for a single…

Updated December 15, 2025

How 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

How 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

AI 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

I'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

Real-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

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

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

For 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 16, 2025

I’ve been building data systems long enough to see the same problem repeat itself. Each wave of analytics promises speed and simplicity. Self-service BI promised freedom from IT. Cloud warehouses promised infinite scale. Now GenAI promises conversational, real-time access to…