Merge pull request #54521 from MicrosoftDocs/main

Auto Publish – main to live - 2026-05-01 17:00 UTC

Author: learn-build-service-prod[bot]

learn-pr/paths/design-manage-semantic-models-fabric/index.yml

@@ -0,0 +1,35 @@
+### YamlMime:LearningPath
+uid: learn.wwl.design-manage-semantic-models-fabric
+metadata:
+  title: Design and Manage Semantic Models in Microsoft Fabric
+  description:  Create semantic models that serve reliable, governed analytics at scale — from initial DAX logic through performance optimization, data access control, and automated lifecycle management.
+  ms.date: 04/30/2026
+  author: angierudduck
+  ms.author: anrudduc
+  ms.topic: learning-path
+  ai-usage: ai-generated
+title: Design and manage semantic models in Microsoft Fabric
+prerequisites: |
+  - Experience building reports in Power BI
+  - Familiarity with DAX syntax including measures and calculated columns
+  - Understanding of dimensional data modeling design concepts
+summary: |
+  Create semantic models that serve reliable, governed analytics at scale — from initial DAX logic through performance optimization, data access control, and automated lifecycle management.
+iconUrl: /training/achievements/generic-trophy.svg
+levels:
+- intermediate
+roles:
+- data-analyst
+products:
+- fabric
+subjects:
+- data-analytics
+- data-modeling
+modules:
+- learn-bizapps.dax-power-bi-create-calculations
+- learn.wwl.design-semantic-models-scale
+- learn.wwl.optimize-semantic-model-performance
+- learn.wwl.enforce-semantic-model-security
+- learn.wwl.manage-semantic-model-lifecycle
+trophy:
+  uid: learn.wwl.design-manage-semantic-models-fabric.trophy

learn-pr/paths/design-transform-analytics-data/index.yml

@@ -0,0 +1,38 @@
+### YamlMime:LearningPath
+uid: learn.wwl.design-transform-analytics-data
+metadata:
+  title: Design and Transform Analytics Data in Microsoft Fabric
+  description: Design dimensional models and apply transformations using dataflows, Spark notebooks, and T-SQL to produce consistent, analysis-ready data in Microsoft Fabric.
+  ms.date: 04/30/2026
+  author: angierudduck
+  ms.author: anrudduc
+  ms.topic: learning-path
+  ai-usage: ai-generated
+title: Design and transform analytics data in Microsoft Fabric
+prerequisites: |
+  - Experience working with data stores such aslakehouses or warehouses
+  - Familiarity with SQL query syntax
+  - Understanding of data modeling concepts such as tables, relationships, and keys
+summary: |
+  Design dimensional models and apply transformations using dataflows, Spark notebooks, and T-SQL to produce consistent, analysis-ready data in Microsoft Fabric.
+iconUrl: /training/achievements/generic-trophy.svg
+levels:
+- intermediate
+roles:
+- data-analyst
+- data-engineer
+products:
+- fabric
+subjects:
+- data-analytics
+- data-engineering
+- data-integration
+- data-modeling
+modules:
+- learn.wwl.choose-data-store-fabric
+- learn.wwl.design-dimensional-models-fabric
+- learn.wwl.fabric-transform-data-dataflows
+- learn.wwl.fabric-transform-data-notebooks
+- learn.wwl.fabric-transform-data-tsql
+trophy:
+  uid: learn.wwl.design-transform-analytics-data.trophy

learn-pr/paths/explore-analytics-data-stores/index.yml

@@ -0,0 +1,34 @@
+### YamlMime:LearningPath
+uid: learn.wwl.explore-analytics-data-stores
+metadata:
+  title: Explore Analytics Data Stores in Microsoft Fabric
+  description: Understand how Microsoft Fabric unifies analytics storage through OneLake, and evaluate when to use lakehouses, warehouses, or eventhouses for your data workloads.
+  ms.date: 04/30/2026
+  author: angierudduck
+  ms.author: anrudduc
+  ms.topic: learning-path
+  ai-usage: ai-generated
+title: Explore analytics data stores in Microsoft Fabric
+prerequisites: |
+  - Familiarity with data concepts and terminology
+summary: |
+  Understand how Microsoft Fabric unifies analytics storage through OneLake, and evaluate when to use lakehouses, warehouses, or eventhouses for your data workloads.
+iconUrl: /training/achievements/generic-trophy.svg
+levels:
+- beginner
+roles:
+- data-analyst
+- data-engineer
+products:
+- fabric
+subjects:
+- data-analytics
+- data-engineering
+modules:
+- learn.wwl.introduction-end-analytics-use-microsoft-fabric
+- learn.wwl.discover-data-onelake
+- learn.wwl.get-started-lakehouses
+- learn.wwl.get-started-data-warehouse
+- learn.wwl.get-started-kusto-fabric
+trophy:
+  uid: learn.wwl.explore-analytics-data-stores.trophy

learn-pr/paths/prepare-ai-ready-analytics-data/index.yml

@@ -0,0 +1,34 @@
+### YamlMime:LearningPath
+uid: learn.wwl.prepare-ai-ready-analytics-data
+metadata:
+  title: Prepare AI-Ready Analytics Data in Microsoft Fabric
+  description: Prepare your semantic layer for AI by adding metadata and linguistic context to gold-layer data stores and semantic models, then generate ontologies that AI agents use to answer business questions.
+  ms.date: 04/30/2026
+  author: angierudduck
+  ms.author: anrudduc
+  ms.topic: learning-path
+  ai-usage: ai-generated
+title: Prepare AI-ready analytics data in Microsoft Fabric
+prerequisites: |
+  - Experience designing and publishing semantic models in Microsoft Fabric
+  - Familiarity with DAX measures and relationships in semantic models
+  - Basic understanding of how AI agents consume structured data
+summary: |
+  Prepare your semantic layer for AI by adding metadata and linguistic context to gold-layer data stores and semantic models, then generate ontologies that AI agents use to answer business questions.
+iconUrl: /training/achievements/generic-trophy.svg
+levels:
+- intermediate
+roles:
+- data-analyst
+- data-engineer
+products:
+- fabric
+subjects:
+- data-analytics
+- data-modeling
+modules:
+- learn.wwl.fabric-prepare-semantic-layer
+- learn.wwl.understand-fabric-iq-fundamentals
+- learn.wwl.create-ontology-with-fabric-iq
+trophy:
+  uid: learn.wwl.prepare-ai-ready-analytics-data.trophy

learn-pr/paths/purview-data-security-posture-management/index.yml

@@ -0,0 +1,37 @@
+### YamlMime:LearningPath
+uid: learn.wwl.purview-data-security-posture-management
+metadata:
+  title: Reduce Data Exposure Risk with Data Security Posture Management in Microsoft Purview
+  description: Reduce data exposure risk by using Data Security Posture Management in Microsoft Purview to assess posture, protect sensitive data, and investigate risks.
+  ms.date: 05/01/2026
+  author: wwlpublish
+  ms.author: riswinto
+  ms.topic: learning-path
+title: Reduce data exposure risk with Data Security Posture Management in Microsoft Purview
+summary: |
+  Data Security Posture Management (DSPM) in Microsoft Purview helps you understand where sensitive data is exposed and how risk is distributed across your environment. You start by exploring DSPM as a unified posture layer, then assess your organization's data security posture. Finally, you protect sensitive data with security objectives and investigate risks when they arise.
+prerequisites: |
+  - Familiar with the Microsoft Purview portal and its navigation
+  - Working knowledge of sensitivity labels and information protection policies
+  - Working knowledge of data loss prevention (DLP) policies and concepts
+  - Working knowledge of Insider Risk Management concepts
+  - Basic understanding of data classification with sensitive information types and trainable classifiers
+iconUrl: /training/achievements/generic-trophy.svg
+levels:
+- intermediate
+roles:
+- administrator
+- risk-practitioner
+products:
+- microsoft-purview
+- m365
+subjects:
+- threat-protection
+- security
+modules:
+- learn.wwl.purview-data-security-posture-management-understand
+- learn.wwl.purview-dspm-assess-data-security-posture
+- learn.wwl.purview-data-security-posture-management-protect-remediate
+
+trophy:
+  uid: learn.wwl.purview-data-security-posture-management.trophy

learn-pr/paths/secure-govern-analytics-data/index.yml

@@ -0,0 +1,35 @@
+### YamlMime:LearningPath
+uid: learn.wwl.secure-govern-analytics-data
+metadata:
+  title: Secure and Govern Analytics Data in Microsoft Fabric
+  description: Implement layered access controls across Microsoft Fabric workspaces and data stores, then establish governance policies that help consumers identify trustworthy, certified analytics assets.
+  ms.date: 04/30/2026
+  author: angierudduck
+  ms.author: anrudduc
+  ms.topic: learning-path
+  ai-usage: ai-generated
+title: Secure and govern analytics data in Microsoft Fabric
+prerequisites: |
+  - Experience administering Microsoft Fabric workspaces
+  - Familiarity with role-based access control concepts
+  - Understanding of data sensitivity classification and labeling
+summary: |
+  Implement layered access controls across Microsoft Fabric workspaces and data stores, then establish governance policies that help consumers identify trustworthy, certified analytics assets.
+iconUrl: /training/achievements/generic-trophy.svg
+levels:
+- intermediate
+roles:
+- data-analyst
+- data-engineer
+products:
+- fabric
+subjects:
+- data-analytics
+- data-management
+modules:
+- learn-wwl.secure-data-access-in-fabric
+- learn-wwl.secure-data-warehouse-in-microsoft-fabric
+- learn.fabric-data-governance-purview
+- learn.wwl.fabric-govern-analytics-data
+trophy:
+  uid: learn.wwl.secure-govern-analytics-data.trophy

learn-pr/wwl-data-ai/secure-data-access-in-fabric/5-exercise-secure-data-access.yml

@@ -8,6 +8,6 @@ metadata:
   author: wwlpublish
   ms.author: theresai
   ms.topic: unit
-durationInMinutes: 30
+durationInMinutes: 45
 content: |
   [!include[](includes/5-exercise-secure-data-access.md)]

learn-pr/wwl-data-ai/store-manage-containers-azure-container-registry/1-introduction.yml

@@ -8,6 +8,7 @@ metadata:
   author: jeffkoms
   ms.author: jeffko
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 3
 content: |
   [!include[](includes/1-introduction.md)]

learn-pr/wwl-data-ai/store-manage-containers-azure-container-registry/2-image-storage.yml

@@ -8,6 +8,7 @@ metadata:
   author: jeffkoms
   ms.author: jeffko
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 8
 content: |
   [!include[](includes/2-image-storage.md)]

learn-pr/wwl-data-ai/store-manage-containers-azure-container-registry/3-build-run-acr-tasks.yml

@@ -8,6 +8,7 @@ metadata:
   author: jeffkoms
   ms.author: jeffko
   ms.topic: unit
+  zone_pivot_groups: video-or-text
 durationInMinutes: 10
 content: |
   [!include[](includes/3-build-run-acr-tasks.md)]