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Welcome to Microsoft Fabric — Real Time Intelligence: Day 1

Use Case 01: Digital Twin Builder for Contoso Energy — Contextualizing Data & Visualizing Insights

In this hands-on lab we walk through building a digital twin using Microsoft Fabric’s Real-Time Intelligence capabilities. You’ll learn how to set up a Fabric workspace, create and manage lakehouses, ingest both static and streaming data, model real-world entities with Digital Twin Builder (preview), query data with Kusto Query Language (KQL), and build real-time dashboards to visualize insights.

Scenario: we use bus movement/location data to model buses and stops. By contextualizing streaming telemetry with static geography/borough data, we estimate delays (e.g., will a bus be late to the next stop?) and reveal stop- and borough-level delay patterns.

What you'll learn

Setup a Microsoft Fabric workspace and core components (Lakehouse, Eventhouse).

Ingest and transform contextual (static) and streaming datasets.

Model entities, relationships and ontology with Digital Twin Builder (preview).

Use KQL for real-time analytics and pattern detection.

Build a Real-Time Dashboard to visualize entity time-series and operational insights.

Best practices for entity mapping, relationship definitions, and streaming transformations.

Who this is for

Data engineers, solution architects, IoT / transportation analysts, and anyone interested in real-time analytics with Microsoft Fabric.

Resources & code
Power BI account: https://app.fabric.microsoft.com/
data/repo: https://learn.microsoft.com/en-us/fab...

Documentation: Microsoft Fabric Digital Twin Builder (preview) — https://learn.microsoft.com/en-us/fab...
https://learn.microsoft.com/en-us/fab...

If you liked this video, please Like 👍, Subscribe 🔔 and comment any questions or suggestions for Day 2.

Chapters

0:00 Intro & scenario overview
Set up Fabric workspace + Lakehouse overview
Create Eventhouse (streaming sink) & ingest pipeline
Ingest static contextual data (stops, boroughs)
Streaming bus telemetry ingestion & transformation
Digital Twin Builder — ontology & entity mapping (preview)
KQL queries for latency & delay detection
Build Real-Time Dashboard & visualizations
Summary, best practices, next steps

Connect with Me:

LinkedIn:   / mohammed-muneef  
Twitter: https://x.com/muneefmhm
Web: https://mhmmuneef.com
#MicrosoftFabric #RealTimeIntelligence #DigitalTwin #KQL #Eventhouse #Lakehouse #IoT #DataEngineering #TransitAnalytics