Updated November 17, 2025
How a Semantic Engine Reduces AI Query Costs Without Sacrificing PerformanceReal-time AI analytics feels like the future: instant insights, natural conversation, decisions without delay. But behind the scenes, that future comes with a big catch: every AI query costs money, and those costs compound fast. Many of our customers see…
Updated May 27, 2025
Why Is Power BI Slow with Snowflake? How to Fix Common Performance ProblemsIf your Power BI dashboards feel more like a waiting game than a real-time tool, you're not alone. Many teams struggle with sluggish performance when connecting Power BI to Snowflake. Dashboards that should load in seconds often take minutes. The…
Updated April 17, 2025
Evaluating a Semantic Layer: How Technical Teams Drive ROI Through Smart Data InfrastructurePicking Up From Part 1: Why Technical Evaluation Matters After realizing a semantic layer could solve PrecisionWorks’ biggest data headaches, Alex, a data engineer, moves on to a critical step: evaluating vendors. (Missed the beginning? Catch up on Part 1:…
Updated 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…
Updated March 27, 2025
Breaking Data Silos with Cross-Cloud Federation and Semantic Layers: Key Takeaways from the TDWI Expert PanelRecently, I had the opportunity to join the TDWI expert panel onBreaking Data Silos with Cross-Cloud Federation and Semantic Layers, alongside industry leaders John Korsak, Enterprise Solutions Engineer from Cube, and Fern Halper, TDWI VP Research, Senior Research Director for…
Updated March 25, 2025
Cloud Cost Optimization: Strategies to Reduce Costs & Maximize 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…
Updated August 4, 2022
AtScale + Snowflake: Enable Dimensional Analysis in the Data CloudAtScale’s partnership with Snowflake has dramatically expanded our customers' data processing capabilities — guiding them toward analytics modernization. From delivering analysis-ready data to extending legacy tool services through dialect support, data practitioners can now deliver blazing-fast dimensional analysis to enable…
Updated April 14, 2022
Creating & Fostering a Data-Driven Culture: Lessons from Kolibri Games, Direct Supply, BetMGM, and PayPalDuring another round of interviews with data leaders, I spoke with several industry experts about creating and fostering a data-driven culture. We discussed different data architectures, the gap between data produced and data consumed, data literacy, and more. The data…
Updated April 5, 2022
Optimizing Cloud Analytics: Actionable Insights Series Part IICurated advice from 50+ data leaders, industry experts & customers Over the last 12 months, we've hosted 18 webinars with 50+ industry experts, data leaders, and customers reaching an audience of 25k+ data and analytics community members/professionals. I've decided to…
Updated March 24, 2022
Data Enrichment: Integrating First-Party and Third-Party DataWhen it comes to effectively consuming data for business insights, there are six key areas: data, access, model, analyze, consume, and insights. AtScale’s Data and Analytics Maturity Model Workshop explains how organizations can build the skills and knowledge necessary to…
