Microsoft Fabric Graphs Explained: Graph Models, GQL, and Real Analytics Use Cases
This video walks through the basics of graph data analysis and demonstrates how Microsoft Fabric's new graph capabilities can be used to build and query graphs, focusing on practical examples using customer and order data. Viewers will learn about graph models, nodes, edges, and relationships, as well as how to use GQL for querying graphs within a Fabric Notebook.
Description
Microsoft Fabric now supports graph models and ontologies — but what does that actually mean for your analytics?
In this video, I give a clear, beginner friendly introduction to graph data analysis and show how Fabric’s new graph capabilities work in practice.
We walk through:
• What graph models are and why they matter
• How nodes, edges, and relationships unlock new analytical questions
• What Fabric supports today (including GQL)
• How to build a simple graph using customer and order data
• How to query that graph and access it from a Fabric Notebook
Graphs make relationship driven questions intuitive and powerful, and Fabric’s new preview features bring those capabilities directly into OneLake.
Keep an eye out for an upcoming video on Fabric Ontologies, the graph model powered semantic layer coming to the platform!
Location of Graph Model data and walk-through instructions:
https://learn.microsoft.com/en-us/fabric/graph/quickstart
The GQL Utility module used in the video:
https://github.com/robkerr/BlogProjects/blob/main/fabric_utilities/gql_utils.py
Contents:
0:00 Introduction
0:43 Why Graphs Matter
1:16 Graph Basics
2:07 Fabric Graph Features
2:36 Ontology
2:57 Demo Intro
3:50 Build a Graph
7:13 Query a Graph with GQL
8:13 GQL in a Notebook
8:48 Wrap-up