Putting the "I" Back into BI
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
Long ago when scaling database capacity wasn't as easy as upping (or downing) configuration settings through a user-friendly admin Web page (like the "T-shirt size" with Snowflake), highly-skilled DBAs were a luxury at smaller enterprises, and people at work used to go to Happy Hour in droves, a funny thing might happen at pau hana … Continue reading Correlation is a Hint Towards Causation
I'm in the middle of prepping for my two sessions at Data Modeling Zone 2025 (March 4-6, 2025). Both sessions are very tightly packed with still so much more to say. So I thought I'd write a blog on key takeaways for attendees to read prior to the sessions. One of my sessions is essentially … Continue reading Key Takeaways from My Two Upcoming DMZ 2025 Sessions
The content is a comprehensive exploration of the relationship between Prolog and LLMs (Large Language Models), detailing their differences, strengths, and potential synergies in the field of AI. It discusses the distinctive attributes of Prolog as a deterministic knowledge base and its contrast with LLMs, illustrating scenarios where each excels. The content also delves into the potential of ChatGPT to assist in authoring Prolog and creating logical, methodical systems. Additionally, it references the emergence of the GPT Store, as a manifestation of the original idea of "separation of logic and procedure". The overall tone of the content is informative, educational, and forward-thinking, and it serves as a valuable resource for understanding the intersection of traditional logic-based AI and modern LLMs.
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.
Expanding BI Analyst Horizons with AI In the landscape of Business Intelligence (BI), the integration of AI and advanced reasoning in the enterprise is essential for staying afloat. To fully integrate with AI, traditional BI analysts, accustomed to working with empirical data and generating reports, must now expand their skills to include deeper analysis, evaluation, … Continue reading Exploring the Higher Levels of Bloom’s Taxonomy
Soft Coded Logic 