Updated January 6, 2026
Shifting to a Dimensional Data Modeling Approach Using a Semantic LayerDimensional modeling is a technique for organizing data into facts (the metrics you measure) and dimensions (the context around those metrics), enabling faster, easier analytics. The semantic layer sits above the dimensional model and translates your business rules into consistent…
Updated June 23, 2022
How to Use Excel for Analytics in the CloudDespite having a billion users, Excel is not always thought of as a business intelligence (BI) tool. Yet Excel remains by far the predominant BI consumption platform in enterprise data because its formulas and functions make it a powerful tool…
Updated June 21, 2022
Rethinking Feature Stores to Better Align AI/ML to Business Impact“We are drowning in information, but starved for knowledge.” - John Naisbitt The wheels of commerce are always churning, pushing merchants to find new opportunities, answers to questions, and the next breakthrough strategy to keep growing. One can imagine the…
Updated June 16, 2022
The Future of Metrics Tooling, Open Source and Enterprise: Insights from Transform, Cube Dev, and AtScaleI recently joined a roundtable discussion at the Metrics Store Summit with three business intelligence (BI) entrepreneurs (and good friends). We dived into our approaches in this space, the architecture of our products, the technical aspects to how different data…
Updated June 9, 2022
The Semantics of the Semantic Layer Part 8: Data Platform IntegrationThis is the last post in this blog series, The Semantics of the Semantic Layer, where I discuss the seven core capabilities of a semantic layer. In this blog, I will dive deeper into how a semantic layer should integrate…
Updated June 2, 2022
The Semantics of the Semantic Layer Part 7: Analytics GovernanceThis is the seventh blog in my blog series, The Semantics of the Semantic Layer, where I discuss the seven core capabilities of a semantic layer. In this blog, I will dive deeper into the analytics governance and security capabilities…
Updated May 31, 2022
Deliver Self-Service BI at scale with the Semantic Layer + DatabricksI recently had the opportunity to sit down for a tech talk with an extraordinary guest: Franco Patano, the lead product specialist for Databricks SQL. We had a great conversation about how a semantic layer can work with the Databricks…
Updated May 26, 2022
The Semantics of the Semantic Layer Part 6: Performance OptimizationThis is the sixth blog in my blog series, The Semantics of the Semantic Layer, where I discuss the seven core capabilities of a semantic layer. In this blog, I will dive deeper into the autonomous performance optimization capabilities that…
Updated May 19, 2022
The Semantics of the Semantic Layer Part 5: The Calculation EngineThis is the fifth blog in my series The Semantics of the Semantic Layer, where I discuss the seven core capabilities of a semantic layer. In this blog, I will dive deeper into the multidimensional calculation engine that serves as…
Updated May 17, 2022
The softer side of enterprise analytics: Culture, Org Design, Process ManagementMany companies pursuing a path to data-driven decision-making – accelerated through data democratization – struggle with how to define and support the core people, roles, and competencies involved with data (data creators, enablers, and consumers). In many cases, the path…
Updated May 12, 2022
The Semantics of the Semantic Layer Part 4: Data PreparationThis is the fourth blog in my blog series, The Semantics of the Semantic Layer, where I describe the seven core capabilities of a semantic layer. In this blog, I will dive deeper into the virtualized data preparation that makes…
Updated May 10, 2022
Accelerate Data Science and AutoML with a Semantic LayerAt AtScale, we love talking to data and analytics technologists and hearing their stories. We recently hosted a tech talk (presentation and demo) with Ben Taylor, Chief AI Evangelist at DataRobot, about how AtScale and DataRobot can help align AI…
