Putting the "I" Back into BI
Situation Over the past few months there has been a trend to move from referring to "large language models" (LLM) to just "language models". The reason for that is the recognition that small language models (SLM) have clear advantages under certain situations. So "language model" is inclusive of both. And of course, as soon as … Continue reading Long Live LLMs! The Central Knowledge System of Analogy
The transactional unit of meaningful human to human communication is a story. It's the incredibly versatile, somewhat scalable unit by which we teach each other meaningful experiences. Our brains recorded stories well before any hints of our ability to draw and write. We sit around a table or campfire sharing stories, not mere facts. We … Continue reading Stories are the Transactional Unit of Human-Level Intelligence
This is Part 2 of a 3-part series where I make the case that pre-aggregated OLAP is essential in this era of AI. The intent of this post is to describe just enough of how a pre-aggregated OLAP engine works for those who are unfamiliar with this technology: Those who have joined the business intelligence … Continue reading The Ghost of OLAP Aggregations – Part 2 – Aggregation Manager
The phrase “thinking outside the box” traces back to a deceptively simple puzzle: nine dots arranged in a 3×3 grid. The challenge is to draw four straight lines through all the dots without lifting your pencil. Most people fail at first because they instinctively keep their lines inside the square boundary implied by the dots. … Continue reading Outside of the Box AI Reasoning with SVMs
If your entry into the business intelligence (BI) game began after around 2010, it could be difficult to appreciate the value of OLAP cubes (referring mostly to SQL Server Analysis Services MD, ca. 1998-2010), those aggregations, and that MDX query language. In fact, you may have a negative impression of those relics, those "cubes", based … Continue reading The Ghost of OLAP Aggregations – Part 1 – Pre-Aggregation
Enterprise Intelligence and Time Molecules link through the Tuple Correlation Web. Introduction The main takeaway of this blog is an explanation of how my two books, Enterprise Intelligence (June 21, 2024) and the more recently published Time Molecules (June 4, 2025), connect. Time Molecules is a follow-up to my first book, Enterprise Intelligence. It connects … Continue reading BI-Extended Enterprise Knowledge Graphs
As I mentioned in a previous post, Sample From My Talk - NFA, I will be delivering two sessions at the Data Modeling Zone 2025 (DMZ) in Phoenix. It will be happening from Tuesday, March 4, 2025 through Thursday, March 6, 2025. That post included a preview one of my two sessions, Beyond Ontologies and Taxonomies—focusing on … Continue reading Trophic Cascades of AI
This blog advocates investing time in the foundational book "Enterprise Intelligence," emphasizing its painless approach to developing an integrated understanding of business intelligence. It elaborates on the book's themes, including BI's role in transformative AI, the Insight Space Graph, and the Tuple Correlation Web. The book is detailed and offers a 25% discount for readers.
In the latest installment of "Prolog’s Role in the LLM Era," several key topics were covered. These include integrating Prolog with traditional OLTP and OLAP databases, the concept of MetaFacts and MetaRules, and the development environment necessary for executing the exercises. The episode emphasizes the potential for creating dynamic and intelligent systems by combining Prolog with various data sources and advanced reasoning techniques. Through these integrations, real-time decision-making systems can be developed for optimized data processing and logic application, laying the groundwork for a distributed and scalable AI framework.
This blog revisits the traditional "analytics maturity model," providing a new perspective from the book "Enterprise Intelligence." The four analytics maturity levels: Descriptive, Diagnostic, Predictive, and Prescriptive, are explained along with their impact in the AI era. The blog emphasizes the importance of understanding these levels and their role in enterprise intelligence.
Soft Coded Logic 