Databricks 推出 Publish to Power BI：Unity Catalog 指标视图一键发布到 Power BI
做数据分析的朋友注意了，Databricks 这次打通了和 Power BI 的语义层：指标在 Unity Catalog 定义一次，Power BI 报表自动同步，不用再两边维护口径。用 Databricks 加 Power BI 的企业团队可以直接省掉大量重复工作，值得评估上线。
Databricks 宣布推出 Publish to Power BI 功能，支持将 Unity Catalog 中的 metric views（指标视图）直接发布到 Power BI。企业此前需要在 Databricks 和 Power BI 两套工具里分别维护指标口径，容易出现定义不一致的问题。新功能让团队在 Databricks 中定义一次业务指标，报告、仪表盘和 AI agents 就能使用同一套受治理的指标定义。
具体机制上，发布后的 Power BI 语义模型会随 Unity Catalog 中指标定义的更新自动保持同步，无需手工重新导出或重写 DAX 逻辑。这意味着指标口径变更时，下游所有 Power BI 报表自动继承最新定义。
对同时使用 Databricks 做数据平台、Power BI 做报表的企业来说，这项功能消除了跨工具维护指标逻辑的负担，也为基于指标构建的 AI agents 提供了一致的口径来源，与 Snowflake 等平台近年在语义层治理上的布局形成直接竞争。
Introducing Publish to Power BI for Unity Catalog metric views!
Teams can now define business metrics once in Databricks and publish them directly to Power BI, bringing the same governed definitions to the reports, dashboards, and AI agents they already use.
Instead of maintaining metric logic across multiple tools, teams can work from a single source of truth, with Power BI models automatically kept in sync as definitions evolve.
Learn more: https://t.co/E7lgWEcbwP
This report is categorized under AITOP's "Products" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Databricks, Power BI, Unity Catalog, semantic layer.
Source attribution: curated from Databricks (@databricks).
