Tag
Reading Time: 2 minutesThis is the third post in my four-part series about AI transformation. The second covered the role of the data team, and the first covered trust. AI innovation is happening at an extraordinary pace. New models, frameworks, and tools are…
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: 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…
