Blog:
AtScale Technology

Updated August 17, 2026

The five things that matter most when choosing a semantic layer for a modern data stack are use case compatibility, connectivity, security and governance, query performance management, and scalability. Get those right, and a semantic layer becomes the governed source…

Updated April 9, 2025

Organizations that have relied on OLAP cubes for years are hitting a wall. The traditional OLAP approach—great for fast, multidimensional analysis—was never designed for the modern cloud data ecosystem. And with the rise of cloud data platforms like Snowflake, Databricks,…

Updated April 3, 2025

The Rising Cost Challenge for Power BI Customers Organizations across industries rely on Power BI to drive business intelligence and inform strategic decisions. However, as data volumes increase, so do the associated costs. Businesses often face growing expenses related to…

Updated March 31, 2025

Natural language querying (NLQ) has the potential to make data accessible to everyone — not just analysts and data engineers. But in practice, tools like Snowflake Cortex Analyst often deliver inconsistent or inaccurate results. That inconsistency erodes trust, slows adoption,…

Updated March 25, 2025

What is Cloud Cost Optimization? Cloud cost optimization is the practice of reducing cloud expenses while maintaining performance and scalability. It involves analyzing cloud usage, right-sizing resources, implementing automation, and leveraging cost-saving tools to maximize efficiency. The goal is to…

Updated March 13, 2025

Despite heavy investments in Snowflake's modern data platform, many business users still default to Excel for day-to-day analysis. The result? Stale extracts, inconsistent KPIs, and a frustrating disconnect between centralized data and the tools people actually use. The AtScale semantic…

Updated March 6, 2025

Getting inconsistent or inaccurate results from Snowflake Cortex Analyst? You’re not alone. While Cortex Analyst’s text-to-SQL engine often boasts over 90% accuracy, real-world use cases frequently expose gaps in precision, context, and consistency. The culprit — a missing semantic layer.…

Updated March 4, 2025

Kyle Hale, Lead Product Architect with Databricks, coined the term "Semantic Lakehouse" in a 2022 blog. The blog explained how to extend the Lakehouse offering to users at the “top of the stack” leveraging PowerBI. The following year, in a…

Updated March 4, 2025

AtScale and Databricks first started partnering together in early 2022. At the time, Databricks SQL was relatively new, and many of their customers were still leveraging optional presentation layers to support Business Intelligence workloads. The partnership began to gain momentum.…

Updated February 19, 2025

Summary AtScale and Snowflake Cortex Analyst have joined forces to enable AI-driven natural language querying (NLQ) on governed semantic models. This integration ensures accurate, consistent SQL generation, aligning AI-driven queries with business definitions. AtScale acts as the governance layer, optimizing…

Updated February 11, 2025

In my last post, I demonstrated the many advantages of using AtScale Models to power your Business Intelligence workloads, including human-friendly SML syntax, Git integration, multi-tool support, zero-extract Live Connections, and proven BI Modeling capabilities. In this post, I'll demonstrate…

Updated January 16, 2025

The fields of Artificial Intelligence (AI) and Business Intelligence (BI) are undergoing rapid transformation, driven by advancements in machine learning, large language models (LLMs), and data democratization. Amid this evolution, open-source semantics are emerging as a cornerstone for bridging the…