Refocus module on visualization, remove refresh unit, add nodes/edges explanation

- Renamed module to 'Visualize ontology data' (removed 'query')
- Changed Query Builder framing from 'querying' to 'filtering and exploring'
- Removed Unit 5 (Refresh graph model) - trivial operation highlighting product limitation
- Renumbered units 6-8 to 5-7 for sequential ordering
- Added 'Understand graph structure: nodes and edges' section to Unit 2
- Updated all references from 'query' to 'explore/filter/visualize' throughout
- Removed refresh content from introduction and summary units

Author: theresa-i

learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/1-introduction.yml

@@ -3,7 +3,7 @@ uid: learn.wwl.visualize-query-ontology-fabric-iq.introduction
 title: Introduction
 metadata:
   title: Introduction
-  description: Introduction to visualizing and querying ontology data with Microsoft Fabric IQ using the relationship graph and Query builder.
+  description: Introduction to visualizing ontology data with Microsoft Fabric IQ using the relationship graph and Query builder to explore connected business concepts.
   ms.date: 03/30/2026
   author: theresa-i
   ms.author: theresai

learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/4-query-ontology-query-builder.yml

@@ -1,9 +1,9 @@
 ### YamlMime:ModuleUnit
 uid: learn.wwl.visualize-query-ontology-fabric-iq.query-ontology-query-builder
-title: Query ontology data with the Query builder
+title: Filter and explore with the Query builder
 metadata:
-  title: Query Ontology Data with the Query Builder
-  description: Learn how to use the Query builder in Microsoft Fabric IQ to add filters, control components, run cross-source queries, and interpret results in Diagram, Card, and Table view.
+  title: Filter and Explore with the Query Builder
+  description: Learn how to use the Query builder in Microsoft Fabric IQ to add filters, control components, explore cross-source data, and interpret results in Diagram, Card, and Table view.
   ms.date: 03/30/2026
   author: theresa-i
   ms.author: theresai

learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/5-exercise-query-ontology.yml

@@ -0,0 +1,16 @@
+### YamlMime:ModuleUnit
+uid: learn.wwl.visualize-query-ontology-fabric-iq.exercise-query-ontology
+title: Exercise - Explore ontology across data sources
+metadata:
+  title: Exercise - Explore Ontology Across Data Sources
+  description: Practice using the Query builder in Microsoft Fabric IQ to answer a business question by adding filters, selecting components, and exploring connected data through visualization.
+  ms.date: 03/30/2026
+  author: theresa-i
+  ms.author: theresai
+  ms.topic: unit
+  ai-usage: ai-generated
+azureSandbox: false
+labModal: false
+durationInMinutes: 20
+content: |
+  [!include[](includes/5-exercise-query-ontology.md)]

learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/5-refresh-graph-model.yml

@@ -1,9 +1,9 @@
 ### YamlMime:ModuleUnit
 uid: learn.wwl.visualize-query-ontology-fabric-iq.exercise-query-ontology
-title: Exercise - Query ontology across data sources
+title: Exercise - Explore ontology across data sources
 metadata:
-  title: Exercise - Query Ontology Across Data Sources
-  description: Practice using the Query builder in Microsoft Fabric IQ to answer a business question by adding filters, selecting components, and interpreting graph query results.
+  title: Exercise - Explore Ontology Across Data Sources
+  description: Practice using the Query builder in Microsoft Fabric IQ to answer a business question by adding filters, selecting components, and exploring connected data through visualization.
   ms.date: 03/30/2026
   author: theresa-i
   ms.author: theresai

learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/6-exercise-query-ontology.yml

@@ -13,4 +13,4 @@ azureSandbox: false
 labModal: false
 durationInMinutes: 2
 content: |
-  [!include[](includes/8-summary.md)]
+  [!include[](includes/7-summary.md)]

…ontology-fabric-iq/7-knowledge-check.yml …ontology-fabric-iq/6-knowledge-check.ymllearn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/7-knowledge-check.yml renamed to learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/6-knowledge-check.yml learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/7-knowledge-check.yml renamed to learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/6-knowledge-check.yml

@@ -1,9 +1,7 @@
 Imagine you're a data analyst at Lamna Healthcare. You've spent the past few weeks building an ontology in Fabric IQ. Hospital, Department, Room, Patient, and VitalSignEquipment entity types are defined, bound to the lakehouse and eventhouse, and structurally sound. Now comes the reason you built it.
 
-The clinical operations manager stops by with a question: "Which rooms in the Cardiology department currently have patients, and which vital sign monitors are active there?" Before the ontology, answering that question meant writing a multi-table SQL join—linking patient assignment records to rooms, rooms to departments, and departments to equipment logs. With the ontology in place, the same question becomes a graph query that follows named relationships across your semantic layer, no joins required.
+The clinical operations manager stops by with a question: "Which rooms in the Cardiology department currently have patients, and which vital sign monitors are active there?" Before the ontology, answering that question meant writing a multi-table SQL join—linking patient assignment records to rooms, rooms to departments, and departments to equipment logs. With the ontology in place, you can explore the answer visually by following named relationships across your semantic layer, no joins required.
 
-In this module, you open the entity type overview to inspect the entity instances that your data bindings have populated. You see individual Department, Room, and Patient records drawn from your OneLake sources. You expand the relationship graph to visualize how those instances connect—patients assigned to rooms, rooms belonging to departments, equipment monitoring patients. You use the Query builder to add filters for specific property values, control which entity types and relationship types appear using the Components pane, and run queries that span your lakehouse and eventhouse without writing any SQL.
-
-You also learn how to keep the graph current. When upstream data in your lakehouse or eventhouse changes, the graph model doesn't update automatically. You explore when schema changes trigger automatic re-ingestion and when data changes require a manual or scheduled refresh—and how to set that schedule.
+In this module, you open the entity type overview to inspect the entity instances that your data bindings have populated. You see individual Department, Room, and Patient records drawn from your OneLake sources. You expand the relationship graph to visualize how those instances connect—patients assigned to rooms, rooms belonging to departments, equipment monitoring patients. You use the Query builder to add filters for specific property values, control which entity types and relationship types appear using the Components pane, and explore data that spans your lakehouse and eventhouse without writing any SQL.
 
 By the end of this module, you're equipped to turn the ontology into answers: exploring connected healthcare data the way business users think about it.

…e-query-ontology-fabric-iq/8-summary.yml …e-query-ontology-fabric-iq/7-summary.ymllearn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/8-summary.yml renamed to learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/7-summary.yml learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/8-summary.yml renamed to learn-pr/wwl-data-ai/visualize-query-ontology-fabric-iq/7-summary.yml

@@ -1,5 +1,38 @@
 The ontology you built in the previous module now contains populated data. Each entity type definition has become a collection of entity instances—real records from your lakehouse tables and eventhouse streams. Exploring how those instances appear is the first step in getting value from your ontology.
 
+## Understand the graph structure: nodes and edges
+
+Your ontology is a graph database—a data structure built from two fundamental elements: **nodes** and **edges**.
+
+### Nodes represent entities
+
+A **node** is an entity instance in your graph. When you defined the Patient entity type and bound it to your lakehouse table, each row in that table became a node in the graph. Patient ID 12345 is a node. The Cardiology department is a node. Room 301 is a node.
+
+Nodes have:
+- **Labels** (the entity type, like Patient or Department)
+- **Properties** (attributes like fullName, departmentName, or roomNumber)
+- **A unique identity** (the key property value that distinguishes this instance from all others)
+
+In graph terminology, your "entity instances table" is showing you a list of nodes of one type.
+
+### Edges represent relationships
+
+An **edge** (also called a relationship) is the connection between two nodes. When you defined the "assigned_to" relationship between Patient and Room, you created the potential for edges. When Patient 12345 checks into Room 301, that specific connection becomes an edge in the graph.
+
+Edges have:
+- **A direction** (Patient → Room, not Room → Patient)
+- **A type** (assigned_to, located_in, monitors)
+- **Source and target nodes** (the two instances being connected)
+- Optionally, **properties** (like admissionDate or transferReason)
+
+The "relationship graph" you see in the overview is a visual representation of nodes and edges: entity instances appear as circles (nodes), and the lines connecting them are the relationships (edges).
+
+### Why this matters
+
+Traditional relational databases answer questions by joining tables. Graph databases answer questions by traversing edges between nodes. When you ask "Which patients are in Cardiology?", the graph query starts at the Cardiology node, follows "has" edges to Room nodes, then follows "assigned_to" edges to Patient nodes. No joins. No foreign key lookups. Just following the connections that already exist.
+
+This graph structure is what makes your ontology powerful—and it's what you're about to explore.
+
 ## Open the entity type overview
 
 The entity type overview is your starting point for exploring any entity type's instances and connections. To open it, select an entity type in the **Entity Types** pane—for example, **Department**—and then select **Entity type overview** from the ribbon.