Search Results
Reading Time: 2 minutesThe recent Iran-Israel conflict is beginning to reshape the economics of enterprise technology. A sustained energy shock is raising fuel, transport, and input costs, hardening inflation expectations and making capital more selective, just as investors grow less tolerant of long…
Reading Time: 3 minutesAll technologies go through a hype cycle — and the data Lakehouse is no exception. After years of aggressive migration push by vendors, many organizations are experiencing Lakehouse Fatigue. They’ve moved data, paid the migration bill, and are still waiting…
Reading Time: 3 minutesThis is the second post in my four-part series about AI transformation. The first covered trust, the most important ingredient in this transformation. As enterprises push toward AI-driven operations, data teams are facing a new mandate. In the past, their…
Reading Time: 3 minutesAcross nearly every industry, organizations are racing to transform how they operate with AI. But despite billions of dollars in investment, real-world results have often been disappointing. Studies consistently show that a significant number of AI initiatives fail to reach…
Reading Time: 3 minutesIn the first part of this series, I provided an introduction to semantic modeling, covering the power of the maieutic approach. In this post, I’ll look into one of the fundamental difficulties of semantic modeling: Its ongoing, iterative nature. “My…
Reading Time: 4 minutesBusiness users want simple answers to apparently simple questions, such as “What counts as a customer, or revenue?” or “Which KPIs can I trust?” and it is up to the data professional, the data architect, or analytics leads, to create…
Reading Time: 2 minutes“…greater than 80% of IT leaders believe their enterprise data is not ready for agentic AI…” – Gartner, from “Innovation Guide for AI Agents” Agentic AI holds great promise, but as this quote from Gartner makes clear, success has been…
Reading Time: 5 minutesFor years, enterprise data architecture has relied on collecting, transforming, and replicating data across multiple systems to serve different analytical and operational needs. This approach has delivered value, but it has also introduced unwanted side effects, over time: unnecessarily duplicated…
Reading Time: 3 minutesSemantic models, logical data architectures, and why Denodo is the ideal companion for traditional AI, generative AI, and RAG Artificial intelligence has made extraordinary progress in recent years. From predictive models to generative systems capable of producing text, images, and…
Reading Time: 4 minutesThe AI landscape is evolving fast. In just the past year, we’ve seen a shift from traditional AI models that respond to prompts, to AI agents that act autonomously, reason in real time, and make decisions across complex systems. But…
