An Interlude Before the Third Act of “The Assemblage of AI”

In the conclusion of my last blog, Chains of Unstable Correlations, I wrote: When you work around experts long enough, you notice that experts sometimes (usually?) forget what isn’t obvious to non-experts. Conversely, people in the field often see things experts overlook because they live inside the operational texture of the system. After a conversation … Continue reading An Interlude Before the Third Act of “The Assemblage of AI” →

The Ghost of OLAP Aggregations – Part 2 – Aggregation Manager

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 Ghost of OLAP Aggregations – Part 1 – Pre-Aggregation

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 →

Prolog and Business Intelligence – Prolog’s Role in the LLM Era, Part 5

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.

The Role of OLAP Cubes in “Enterprise Intelligence”

In the pursuit of data-driven excellence, quick and well-informed decision-making is crucial for enterprises. Online Analytical Processing (OLAP) facilitates this by enabling rapid analysis of multidimensional data. Despite challenges from big data and cloud technologies, OLAP's role has resurged in managing vast data volumes, supporting complex analysis, and bridging structured and unstructured data for enterprise intelligence.

The Ghost of MDX

Practically every customer over my 20+ years working with SQL Server Analysis Services (SSAS) has told me "MDX is hard to learn". As cliche as this is to say, I think the source of difficulty is mostly that the MDX language is misunderstood. I believe that in large part, it's because SQL and MDX are … Continue reading The Ghost of MDX →

OLAP is Back as Kyvos Insights

In 2013 I wrote a blog titled, Is OLAP Terminally Ill? I used the term "Terminally Ill" because I didn't believe that the strategy of managing pre-aggregations was dead. Temporarily unnecessary, maybe, but not dead. To be clear, by "OLAP" (Online Analytical Processing), I meant in both contexts of the software named SQL Server Analysis … Continue reading OLAP is Back as Kyvos Insights →