A traditional semantic layer in the context of BI is great for specific metric definitions (like revenue, churn, ARPU). However, they are usually hand constructed by data teams using very specific syntax through a dedicated layer like LookML and are connected directly to a BI tool like Looker.
令人惊讶的是：商业智能(BI)中的传统语义层虽然对特定指标定义很有用，但通常是由数据团队手动构建的，使用特定的语法如LookML，并直接连接到BI工具如Looker。这种手动构建方式与现代AI系统所需的自动化和灵活性形成鲜明对比，揭示了传统数据工具与现代AI需求之间的根本冲突。