June 3, 2025
AtScale 2025 Product Announcements: A Smarter, Faster, More Open Semantic LayerThe 2025 Semantic Layer Summit was more than a virtual event—it was a product showcase for the future of semantic modeling. AtScale unveiled its most significant updates yet, delivering innovations that make the semantic layer smarter, more interoperable, and GenAI-ready.…
May 9, 2025
How Multinational Enterprises Can Solve the Currency Conversion Challenge with a Semantic LayerFor multinational enterprises, currency conversion is more than just a finance function—it’s a complex data modeling challenge that directly impacts revenue reporting, profitability analysis, and strategic planning. Exchange rates fluctuate constantly, and without a flexible, scalable approach to managing them,…
April 22, 2025
How Vodafone Portugal Transformed Telecom Analytics with AtScale’s Semantic Layer + CelfocusIn telecommunications, data is abundant, but turning it into useful insights can be extremely difficult. Communication Service Providers (CSPs) operate in a fast-paced, highly competitive market, where success depends on efficiently managing massive volumes of data quickly and reliably. But…
April 10, 2025
Top 5 Considerations When Choosing a Semantic Layer for Modern Data StacksUnderstanding the Challenge: A Day in the Life of a Data Engineer Meet Alex, a data engineer at PrecisionWorks, a global manufacturer managing a large-scale enterprise data ecosystem. Every day, Alex battles: Data silos across CRM, ERP, and third-party systems…
April 9, 2025
Modernizing OLAP for the Cloud: Why Legacy BI Needs a Semantic UpgradeOrganizations 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,…
April 3, 2025
How a Typical Power BI Customer Can Save Millions in Annual CostsThe 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…
March 31, 2025
Building Trust in NLQ: How to Improve Cortex Analyst Results in SnowflakeNatural 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,…
March 25, 2025
Cloud Cost Optimization: Strategies for Maximizing EfficiencyWhat 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…
March 13, 2025
Excel + Snowflake: How AtScale Helps Bridge the Gap Between Data Warehouse and Spreadsheet AnalysisDespite 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…
March 6, 2025
Troubleshooting Snowflake Cortex Analyst: Why Your Results Aren’t AccurateGetting 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.…
