Putting the "I" Back into BI
Welcome to the Prolog in the LLM Era Spring Break Special! Starring ... decoupled recognition and action ... event streaming ... correlation doesn't imply causation ... and our special guest star ... Deductive Time Travel!!! Notes before diving in: Please see Part 1 in the series for background on Prolog if you're not familiar with … Continue reading Closer to Causation – Prolog in the LLM Era – Spring Break Special
Introduction: Structuring OODA Loop for Real-World Decision Intelligence Decision-making isn’t just about research—it also involves adapting to change faster than the competition, seizing what can be ephemeral openings for opportunity. The OODA loop—Observe, Orient, Decide, Act—is a well-known model for this, originally developed for military strategy but applicable everywhere from business intelligence to AI-driven automation. … Continue reading Beyond Ontologies: OODA Loop Knowledge Graph Structures
This is a sneak peek of my upcoming book, Time Molecules: The BI Side of Process Mining and Systems Thinking—to be published in the May-June 2025 timeframe. I’ve long been fascinated by systems thinking, ever since reading The Fifth Discipline, Peter Senge, when it was first released. The idea that complex systems behave in ways … Continue reading Sneak Peek at My New Book—Time Molecules
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
Think about the usual depiction of a network of brain neurons. It’s almost always shown as a sprawling, kind of amorphous web, with no real structure or organization—just a big ball of connected neurons (like the Griswold Christmas lights). But this image misses so much of what makes the brain remarkable. Neurons aren’t just randomly … Continue reading Embedding Machine Learning Models into Knowledge Graphs
This post maps the ideas in the recent paper Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention (Munkhdalai, T., Faruqui, M., & Gopal, S. 2024) to concepts from my book, Enterprise Intelligence, including the Tuple Correlation Web (TCW), Insight Space Graph (ISG), and cubespace as a semantic layer. In business intelligence (BI) and … Continue reading The BI Counterpart to AI Infinite Context
I’m in the first week of recovery from a pacemaker implant. My wife, primary care physician, ChatGPT, and I had been wracking our brains trying to diagnose the residual effects of a very odd and serious event I experienced in early October (2024). Every test came back negative. The last result to arrive (Nov 14, … Continue reading A Data Guy’s Pacemaker Experience
The content discusses the significance of historical context in learning and decision-making, emphasizing the value of Prolog as a tool to understand complex logical rules over time. It explores how expert knowledge and decision-making evolve, and how modern technology can facilitate the integration of historical insights into artificial intelligence, enabling enriched decision-making today.
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.
The author recounts the challenges of pitching a product during the dot-com bubble burst, paralleling it with current skepticism towards AI. Despite the doubts, the book "Enterprise Intelligence" argues that AI, though not without flaws, can greatly enhance enterprise analytics. It emphasizes a balanced approach and offers practical knowledge for leveraging AI in business.
Soft Coded Logic 