Fixed headers, image tags and selected verbiage

Author: theresa-i

learn-pr/wwl-data-ai/understand-fabric-iq-fundamentals/5-knowledge-check.yml

@@ -4,7 +4,7 @@ title: Module assessment
 metadata:
   title: Module assessment
   module_assessment: true
-  ai_genearted_module_assessment: true
+  ai_generated_module_assessment: true
   description: "Check your knowledge of Microsoft Fabric IQ fundamentals"
   ms.date: 02/02/2026
   author: theresa-i

learn-pr/wwl-data-ai/understand-fabric-iq-fundamentals/includes/1-introduction.md

@@ -1,9 +1,7 @@
-# Introduction
-
 Imagine you're a data analyst at Lamna Healthcare Medical Center, responsible for helping clinical operations teams understand patient care patterns across your facility. Patient records sit in lakehouse tables while vital signs stream continuously from ICU monitoring equipment into an eventhouse. When hospital administrators ask questions like "Which patients in the ICU have elevated vital signs?" or "How many beds are occupied on the surgical floor?", you need to manually join lakehouse tables with eventhouse streams, translate business terms into technical column names, and write complex queries.
 
 Business users can't explore the data themselves—they depend on you to write queries each time they have a question. By the time you deliver answers, clinical conditions may have already changed.
 
-Microsoft Fabric IQ addresses this by providing a way to define business vocabulary in an ontology, then bind those concepts to your data sources in OneLake. You define concepts such as Patient, Department, and Room with their properties and relationships, creating a semantic layer that both data agents and Graph in Microsoft Fabric can use. 
+Fabric IQ solves this challenge by letting you define business vocabulary in an ontology, then bind those concepts to your data sources in OneLake. You define concepts such as Patient, Department, and Room with their properties and relationships, creating a semantic layer. Business users can then ask questions in natural language through data agents, exploring the data themselves without needing you to write queries. 
 
 In this module, you'll discover what Fabric IQ is and how it works. You'll explore the components that work together—ontology items, data agents, Graph in Microsoft Fabric, and Power BI semantic models—and learn when to use each one. You'll also see how ontology modeling shifts your approach from use-case-driven thinking to concept-driven thinking, fundamentally changing how teams collaborate around data.

learn-pr/wwl-data-ai/understand-fabric-iq-fundamentals/includes/2-get-started-with-fabric-iq.md

@@ -1,6 +1,4 @@
-# Get started with Fabric IQ
-
-Fabric IQ is a workload in Microsoft Fabric for creating ontologies that define your business vocabulary. It sits alongside other Fabric workloads like Data Engineering, Data Factory, Data Science, Data Warehouse, Real-Time Intelligence, and Power BI. Within the IQ workload, you create ontology items that establish your enterprise vocabulary.
+Fabric IQ is a workload in Microsoft Fabric for creating ontologies that define your business vocabulary. It sits alongside other Fabric workloads like Data Engineering, Data Factory, Data Science, Data Warehouse, Real-Time Intelligence, and Power BI. Within the IQ workload, you create **ontology items**—Fabric artifacts that contain your ontology definitions and data bindings.".
 
 An ontology is a shared vocabulary of your business. It's made up of the things in your environment (represented as entity types), their facts (represented as properties of entity types), and the ways they connect (represented as relationships).
 

learn-pr/wwl-data-ai/understand-fabric-iq-fundamentals/includes/3-explore-fabric-iq-components.md

@@ -1,5 +1,3 @@
-# Explore Microsoft Fabric IQ components
-
 Microsoft Fabric IQ brings together several components that work as an integrated ecosystem. Each component serves a specific role in how you define, query, analyze, and visualize your business data. Understanding these components helps you choose the right tool for each task and leverage their combined strengths.
 
 Fabric IQ includes four core components:
@@ -29,7 +27,7 @@ You enhance data agent accuracy by providing **data agent instructions** (guidan
 
 Data agents enforce read-only access and apply security protocols to ensure users only see data they have permission to access. You can publish data agents to Microsoft 365 Copilot or integrate them with Microsoft Copilot Studio to extend their reach beyond Fabric.
 
-![Screenshot showing the data agent chat interface with a question and answer.](../media/data-agent-interface.png)
+:::image type="content" source="../media/data-agent-interface.png" alt-text="Screenshot showing the data agent chat interface with a question and answer.":::
 
 ## Graph in Microsoft Fabric: Visualize and traverse relationships
 
@@ -43,7 +41,7 @@ Graph in Microsoft Fabric operates directly on OneLake without requiring data du
 
 Ontology and Graph in Microsoft Fabric work together seamlessly. The ontology declares your business concepts and relationships, then automatically creates a graph structure. Graph in Microsoft Fabric stores and computes the traversals, enabling visual exploration and advanced queries over your connected data.
 
-![Screenshot showing the graph interface for exploring relationships visually.](../media/graph-interface.png)
+:::image type="content" source="../media/graph-interface.png" alt-text="Screenshot showing the graph interface for exploring relationships visually.":::
 
 ## Semantic models: Generate ontologies from existing data models
 

learn-pr/wwl-data-ai/understand-fabric-iq-fundamentals/includes/4-understand-ontology-modeling-paradigm.md

@@ -1,5 +1,3 @@
-# Understand the ontology modeling paradigm
-
 Ontology modeling in Fabric IQ defines business concepts independent of specific analytical use cases. This unit explains how the ontology approach differs from traditional analytical data modeling.
 
 ## Recognize business concepts over table schemas

learn-pr/wwl-data-ai/understand-fabric-iq-fundamentals/index.yml

@@ -10,18 +10,18 @@ metadata:
   ms.service: fabric
   ai-usage: ai-generated
 title: Understand Microsoft Fabric IQ fundamentals
-summary: Microsoft Fabric IQ provides a way to define business vocabulary in ontologies and bind them to data sources. Learn about ontology items, data agents, Graph in Microsoft Fabric, and Power BI semantic models, and discover how ontology modeling shifts from use-case-driven to concept-driven thinking.
+summary: Microsoft Fabric IQ provides a way to define business vocabulary in ontologies and bind them to data sources. Learn about ontology items, data agents, Graph in Microsoft Fabric, and Power BI semantic models. Discover how ontology modeling differs from traditional analytical modeling by starting with business concepts rather than specific use cases.
 abstract: |
   By the end of this module, you'll be able to:
   - Explain what Fabric IQ is and how ontologies define business vocabulary
   - Describe the role of ontology items in creating entity types, properties, and relationships
   - Distinguish between the roles of each Fabric IQ component: ontology items, data agents, Graph in Microsoft Fabric, and Power BI semantic models
   - Compare ontology modeling's concept-driven approach with traditional use-case-driven data modeling
 prerequisites: |
-  The following prerequisites should be completed:
-  - Familiarity with basic data concepts like tables, columns, and relationships
-  - Understanding of business intelligence and analytics scenarios
-  - Basic knowledge of Microsoft Fabric workloads (lakehouse, warehouse, Power BI)
+  Before starting this module, you should have:
+  - Ability to navigate the Microsoft Fabric portal
+  - Conceptual understanding of data concepts such as tables, columns, and relationships
+  - General familiarity with business intelligence and analytics scenarios
 iconUrl: /learn/achievements/generic-badge.svg
 levels:
 - beginner