This podcast episode explores the evolution of semantic layers in data platforms and their impact on data modeling, data delivery, and the responsibilities of data teams. It discusses the shift towards standalone semantic layers and their role in providing a single source of truth for metrics and definitions. The episode also highlights the challenges and benefits associated with the disaggregation of the overall data stack and the adoption process for incorporating a semantic layer. Additionally, it delves into the technical aspects of building a semantic layer and the integration between dbt and Cube. The podcast concludes by discussing the balancing act between open source and commercial product strategies and the role of Cube in data modeling and business intelligence.