Blog

November 10, 2025 / 5 MIN READ

How AI is Transforming Semantic Modeling (and Why It Matters for the Next Generation of Analytics)

Semantic modeling has always been one of the most complex parts of analytics and arguably the most important. It’s the layer where your business defines itself: revenue, margin, customer lifetime value, churn, all of these…

Posted By: Dave Mariani

November 3, 2025 / 7 MIN READ

The Golden Age of the Semantic Layer: Why AI Can’t Work Without Context

For years, the semantic layer quietly sat behind the scenes of enterprise data systems, translating complex data models into the business logic that made them meaningful. It was a critical component for BI teams but…

Posted By: Dave Mariani

October 23, 2025 / 9 MIN READ

ETL vs. ELT: Differences, Pros, Cons, and How to Choose

Data loading seems simple on the surface — move information from here to there. The complexity emerges when you ask: at what stage should transformation occur? Before you load? After? This sequencing question, whether to…

Posted By: Brendan Peterson

October 21, 2025 / 14 MIN READ

7 Modern Data Architecture Principles

Learn the 6 principles of modern data architecture from companies who have recently updated their data architecture. Do you follow these principles?

Posted By: Dave Mariani

October 21, 2025 / 6 MIN READ

Why GigaOm Recognized Universal Semantic Modeling as the Future of AI Analytics

Enterprise teams today are juggling Power BI and Tableau, Python and R, plus a growing collection of AI copilots and agents. The problem? Every tool seems to have its own version of what “revenue per…

Posted By: Brendan Peterson

October 16, 2025 / 8 MIN READ

Scaling AI Without Breaking the Bank: Why Semantic Layers Drive Performance and Cost Efficiency

Scaling AI efficiently comes down to one architectural choice: put a semantic layer, powered by a compute engine like AtScale’s ACE, in front of your warehouse so every query, from a dashboard or a GenAI…

Posted By: Dave Mariani

October 14, 2025 / 19 MIN READ

Best Data Analysis Tools to Use in 2026

June 9th, 2026 update : We’ve updated this article around the biggest shift in analytics: AI agents that do the work for you. A new category, AI Data Analytics CoWork, now leads the list, and…

Posted By: Mark Palmer

October 7, 2025 / 7 MIN READ

From Models to Meaning: Why Semantic Layers Are the Foundation of Enterprise GenAI Success

Enterprise GenAI deployment is accelerating rapidly, with organizations rushing to implement AI copilots, natural language query interfaces, and agentic AI systems across their business workflows. But here’s the hard truth that I’m seeing emerge from…

Posted By: Cort Johnson

October 2, 2025 / 6 MIN READ

Composable Models: Why Composability is the Future of the Semantic Layer

The 2025 GigaOm Semantic Layer Radar Report recognized AtScale as the Leader and Fast Mover for our innovations in composable modeling, open semantics, and AI readiness. Composable models treat every metric and dimension as modular,…

Posted By: Dave Mariani

September 30, 2025 / 9 MIN READ

The CFO's Guide to Data Modernization: Cost Control in the Cloud Era

The CFO’s Evolving Role in Data Strategy If you’re a CFO managing cloud data costs, you’ve likely noticed your monthly bills looking less like predictable line items and more like volatile stock charts. Welcome to…

Posted By: Macaulay Parker

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Blog

How AI is Transforming Semantic Modeling (and Why It Matters for the Next Generation of Analytics)

The Golden Age of the Semantic Layer: Why AI Can’t Work Without Context

ETL vs. ELT: Differences, Pros, Cons, and How to Choose

7 Modern Data Architecture Principles

Why GigaOm Recognized Universal Semantic Modeling as the Future of AI Analytics

Scaling AI Without Breaking the Bank: Why Semantic Layers Drive Performance and Cost Efficiency

Best Data Analysis Tools to Use in 2026

From Models to Meaning: Why Semantic Layers Are the Foundation of Enterprise GenAI Success

Composable Models: Why Composability is the Future of the Semantic Layer

The CFO's Guide to Data Modernization: Cost Control in the Cloud Era