As a developer working on data solutions in Fabric, you frequently create items in workspaces. Previously, by selecting ‘+New’ in the workspace, you can access a drop-down menu with some pre-defined item types to get started. However, when you need to create other types of items, you have to navigate to a new page, which … Continue reading “New Item Panel in Workspace”
We’re thrilled to announce that Fabric Runtime 1.3 has officially moved from Public Preview to General Availability (GA). This is a major upgrade to our Apache Spark-based big data execution engine, which powers both data engineering and data science workflows. Fabric Runtime 1.3 is now fully integrated into the Fabric platform, ensuring a smooth and … Continue reading “Fabric Runtime 1.3 is Generally Available! Upgrade your data engineering and science workloads to harness the latest innovations and performance enhancements”
Introduction: We are excited to announce a significant enhancement to the Tenant Setting Delegation feature in Microsoft Fabric. Tenant setting delegation has existed in some form since the public preview launch of Fabric, primarily allowing delegation of workload controls to capacity admins. We are now introducing the delegation of export settings to workspaces via domain. … Continue reading “Announcing the Enhanced Tenant Setting Delegation for Export Controls in Microsoft Fabric”
The Share capability for Fabric AI Skill is now in public preview. This feature enables AI Skill creators to share their AI Skill with colleagues, allowing them to consume the AI Skill and gain valuable insights from the data. How Sharing WorksOnce you have created and validated the effectiveness of your AI Skill, you can … Continue reading “Announcing Public Preview of the “Share” Feature for Fabric AI Skill”
Guidance to Maximizing Productivity and Efficiency for your Data Engineering Workloads Data engineering teams often grapple with the complexities of planning and configuring compute resources for their data platforms. This is especially true when working with large-scale, complex datasets and demanding downstream SLAs. A one-size-fits-all approach is rarely effective, as different data layers and datasets … Continue reading “Optimizing Spark Compute for Medallion Architectures in Microsoft Fabric”
