Updated May 22, 2026

10 Things We Learned at the 2026 Semantic Layer Summit

Most enterprise AI governance conversations start with LLMs. But when an AI agent returns a wrong answer, the failure usually traces back to a much simpler problem: the business logic behind the answer was never defined in a place the…

Posted by: Dave Mariani

Updated May 7, 2026

Inside the Trillion-Dollar AI Problem: Context and Compute

Snowflake, Tableau, and BlackRock named the symptom. Jeremy Arendt at Blue Yonder is showing operators what it actually costs. Jeremy Arendt runs analytics engineering at Blue Yonder, the supply chain platform behind a meaningful slice of the world's trucks, warehouses,…

Posted by: Mark Palmer

Updated March 27, 2026

AI vs. BI: Differences, What Changed, and Why Semantics Became Critical

Enterprise analytics was never just about data. It was about trust and confidence, getting the right people the right information so they could make intelligent decisions and keep things moving forward. The BI stack was made for that purpose, and…

Posted by: AtScale

Updated March 17, 2026

Why Moving Data for BI and AI Creates Architecture Problems

In modern data architectures, analytics tools often replicate data from the warehouse into secondary systems to improve performance. While this can speed up dashboards, it introduces new problems: duplicated datasets, inconsistent metrics, fragmented governance, and rising cloud costs. Modern analytics…

Posted by: Dave Mariani

Updated July 1, 2025

SSAS Cube Migration to Snowflake: Complete Roadmap

Many organizations are moving away from legacy SQL Server Analysis Services (SSAS) toward modern, cloud-based platforms like Snowflake. But there's a catch: SSAS isn’t just a storage engine — it’s a powerful semantic layer. Without a plan to replace that…

Posted by: Macaulay Parker

Updated May 22, 2026

10 Things We Learned at the 2026 Semantic Layer Summit

Most enterprise AI governance conversations start with LLMs. But when an AI agent returns a wrong answer, the failure usually traces back to a much simpler problem: the business logic behind the answer was never defined in a place the…

Posted by: Dave Mariani

Updated May 7, 2026

Inside the Trillion-Dollar AI Problem: Context and Compute

Snowflake, Tableau, and BlackRock named the symptom. Jeremy Arendt at Blue Yonder is showing operators what it actually costs. Jeremy Arendt runs analytics engineering at Blue Yonder, the supply chain platform behind a meaningful slice of the world's trucks, warehouses,…

Posted by: Mark Palmer

Updated March 27, 2026

AI vs. BI: Differences, What Changed, and Why Semantics Became Critical

Enterprise analytics was never just about data. It was about trust and confidence, getting the right people the right information so they could make intelligent decisions and keep things moving forward. The BI stack was made for that purpose, and…

Posted by: AtScale

Updated March 17, 2026

Why Moving Data for BI and AI Creates Architecture Problems

In modern data architectures, analytics tools often replicate data from the warehouse into secondary systems to improve performance. While this can speed up dashboards, it introduces new problems: duplicated datasets, inconsistent metrics, fragmented governance, and rising cloud costs. Modern analytics…

Posted by: Dave Mariani

Updated July 1, 2025

SSAS Cube Migration to Snowflake: Complete Roadmap

Many organizations are moving away from legacy SQL Server Analysis Services (SSAS) toward modern, cloud-based platforms like Snowflake. But there's a catch: SSAS isn’t just a storage engine — it’s a powerful semantic layer. Without a plan to replace that…

Posted by: Macaulay Parker
Guide: How to Choose a Semantic Layer
The Ultimate Guide to Choosing a Semantic Layer