Merge pull request #53700 from AngieRudduck/warehouse

Updated fabric warehouse module with AI narrative

Author: Carolyn135

learn-pr/wwl/get-started-data-warehouse/1-introduction.yml

@@ -4,9 +4,9 @@ title: Introduction
 metadata:
   title: Introduction
   description: "Introduction"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
 durationInMinutes: 3
 content: |

learn-pr/wwl/get-started-data-warehouse/2-understand-data-warehouse.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.wwl.get-started-data-warehouse.understand-data-warehouse
-title: Understand data warehouse fundamentals
+title: Understand data warehouses
 metadata:
-  title: Understand data warehouse fundamentals
-  description: "Understand data warehouse fundamentals"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  title: Understand Data Warehouses
+  description: "Understand data warehouses"
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
 durationInMinutes: 7
 content: |

learn-pr/wwl/get-started-data-warehouse/3-understand-data-warehouse-fabric.yml

@@ -2,12 +2,12 @@
 uid: learn.wwl.get-started-data-warehouse.understand-data-warehouse-fabric
 title: Understand data warehouses in Fabric
 metadata:
-  title: Understand data warehouses in Fabric
+  title: Understand Data Warehouses in Fabric
   description: "Understand data warehouses in Fabric"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
-durationInMinutes: 6
+durationInMinutes: 8
 content: |
   [!include[](includes/3-understand-data-warehouse-fabric.md)]

learn-pr/wwl/get-started-data-warehouse/4-query-transform-data.yml

@@ -2,11 +2,11 @@
 uid: learn.wwl.get-started-data-warehouse.query-transform-data
 title: Query and transform data
 metadata:
-  title: Query and transform data
+  title: Query and Transform Data
   description: "Query and transform data"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
 durationInMinutes: 6
 content: |

learn-pr/wwl/get-started-data-warehouse/5-model-data.yml

@@ -1,13 +1,13 @@
 ### YamlMime:ModuleUnit
 uid: learn.wwl.get-started-data-warehouse.model-data
-title: Prepare data for analysis and reporting
+title: Model data in a warehouse
 metadata:
-  title: Prepare data for analysis and reporting
-  description: "Prepare data for analysis and reporting"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  title: Model Data in a Warehouse
+  description: "Model data in a warehouse"
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
-durationInMinutes: 6
+durationInMinutes: 7
 content: |
   [!include[](includes/5-model-data.md)]

learn-pr/wwl/get-started-data-warehouse/6-security-monitor.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.wwl.get-started-data-warehouse.security-monitor
-title: Secure and monitor your data warehouse
+title: Secure and monitor a warehouse
 metadata:
-  title: Secure and monitor your data warehouse
-  description: "Secure and monitor your data warehouse"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  title: Secure and Monitor a Warehouse
+  description: "Secure and monitor a warehouse"
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
 durationInMinutes: 4
 content: |

learn-pr/wwl/get-started-data-warehouse/7-exercise.yml

@@ -1,12 +1,12 @@
 ### YamlMime:ModuleUnit
 uid: learn.wwl.get-started-data-warehouse.exercise
-title: Exercise - Analyze data in a data warehouse
+title: Exercise - Create and query a warehouse
 metadata:
-  title: Exercise - Analyze data in a data warehouse
-  description: "Exercise - Analyze data in a data warehouse"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  title: Exercise - Create and Query a Warehouse
+  description: "Exercise - Create and query a warehouse"
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
 durationInMinutes: 30
 content: |

learn-pr/wwl/get-started-data-warehouse/8-knowledge-check.yml

@@ -6,9 +6,9 @@ metadata:
   ai_generated_module_assessment: true
   title: Module assessment
   description: "Knowledge check"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
   module_assessment: true
 durationInMinutes: 3
@@ -48,3 +48,14 @@ quiz:
     - content: "To grant access to individual warehouses for downstream consumption."
       isCorrect: true
       explanation: "Correct.  By granting access to a single data warehouse using item permissions, you can enable downstream consumption of data."
+  - content: "What capability does a Fabric data warehouse provide that a SQL analytics endpoint does not?"
+    choices:
+    - content: "Writing data using INSERT, UPDATE, DELETE, and MERGE statements."
+      isCorrect: true
+      explanation: "Correct. A Fabric data warehouse supports full T-SQL DML, including INSERT, UPDATE, DELETE, and MERGE. A SQL analytics endpoint provides read-only access to lakehouse data."
+    - content: "Reading data from tables and views using SELECT statements."
+      isCorrect: false
+      explanation: "Incorrect. Both a Fabric data warehouse and a SQL analytics endpoint support reading data from tables and views."
+    - content: "Connecting with SQL client tools like SQL Server Management Studio."
+      isCorrect: false
+      explanation: "Incorrect. Both a Fabric data warehouse and a SQL analytics endpoint support connections from standard SQL client tools through TDS connections."

learn-pr/wwl/get-started-data-warehouse/9-summary.yml

@@ -4,9 +4,9 @@ title: Summary
 metadata:
   title: Summary
   description: "Summary"
-  ms.date: 5/15/2025
-  author: JulianePadrao
-  ms.author: jupadrao
+  ms.date: 03/04/2026
+  author: theresa-i
+  ms.author: theresai
   ms.topic: unit
 durationInMinutes: 1
 content: |

learn-pr/wwl/get-started-data-warehouse/includes/1-introduction.md

@@ -1,7 +1,7 @@
-Relational data warehouses are at the center of most enterprise business intelligence (BI) solutions. While the specific details may vary across data warehouse implementations, a common pattern based on a denormalized, multidimensional schema has emerged as the standard design for a relational data warehouse.
+Relational data warehouses are at the center of most enterprise business intelligence (BI) solutions. They provide a structured, SQL-based environment where organizations store, query, and analyze business data at scale.
 
-Microsoft Fabric's data warehouse is a modern version of the traditional data warehouse. It centralizes and organizes data from different departments, systems, and databases into a single, unified view for analysis and reporting purposes. Fabric's data warehouse provides full SQL semantics, including the ability to insert, update, and delete data in the tables. Fabric's data warehouse is unique because it's built on the Lakehouse, which is stored in Delta format and can be queried using SQL. It's designed for use by the whole data team, not just data engineers.
+Microsoft Fabric provides a fully managed data warehouse with full transactional T-SQL capabilities, including the ability to create tables and insert, update, and delete data. Because warehouse data is stored in Delta format on OneLake, it integrates seamlessly with other Fabric workloads. This makes the data warehouse a core component of your end-to-end analytics solution and part of the intelligent data foundation that supports Copilot experiences and AI-driven insights across the platform.
 
-Fabric's data warehouse experience is designed to address these challenges. Fabric enables data engineers, analysts, and data scientists to work together to create and query a data warehouse that is optimized for their specific needs.
+Suppose you work at a retail organization that stores structured business data across multiple systems. Your team needs to centralize this data for analytics and reporting using familiar SQL tools. You need to understand when a Fabric data warehouse is the right choice, how to create one, and how to query and transform data using T-SQL.
 
-In this module, you'll learn about data warehouses in Fabric, create a data warehouse, load, query, and visualize data.
+In this module, you explore the fundamentals of dimensional modeling with fact and dimension tables, then discover what makes Fabric's data warehouse unique, including full T-SQL support with MERGE capabilities, Copilot-assisted query authoring, and seamless integration with OneLake. You practice querying data, structuring tables, and explore the security and monitoring features that keep your warehouse governed and performant. By the end of this module, you'll know how to build a warehouse that serves both human analysts and AI-powered experiences.