Microsoft Fabric introduces a unified SaaS analytics platform that enables organisations to design and operationalise modern lakehouse architectures faster than ever before. But building an effective lakehouse requires more than just tools, it demands a structured approach that connects business requirements, data engineering practices and scalable modelling patterns.

In this full-day hands-on training, participants will learn how to design and implement a complete lakehouse solution in Microsoft Fabric. The day begins with a conceptual introduction to lakehouse principles and the Fabric architecture, followed by the presentation of a realistic business case that will guide all exercises throughout the training.

Attendees will explore multiple data ingestion patterns available in Fabric and gain practical experience by building ingestion pipelines themselves. The session then introduces the medallion architecture and dimensional modelling concepts, enabling participants to design a fit-for-purpose analytical data model based on business requirements while working collaboratively in groups.

Finally, participants will be introduced to Spark and notebook-driven engineering workflows and will implement data transformation processes that move data across Bronze, Silver and Gold layers. The training concludes with a recap of architectural decisions, engineering trade-offs and recommended implementation patterns for production lakehouse environments.

Pre-requisites:
• Understanding of data warehouse/lakehouse concepts such as dimensional modelling
• Know how to read and write SELECT statements in the SQL language (T-SQL or Spark SQL)
• Access to a Fabric tenant with active capacity (trial or otherwise). Any capacity size will work
• Curious mind and willingness to learn

This session is ideal for data engineers, analytics engineers and solution architects who want practical guidance on building scalable lakehouse solutions in Microsoft Fabric.
Structure:
Part 1. Introduction
• Introduction to Lakehouses in Microsoft Fabric
• Business Case Introduction
Part 2. Ingestion
• Data Ingestion Patterns in Microsoft Fabric
• Hands-On Exercise: Ingest data with Fabric Pipeline
Part 3. Data modelling
• Introduction to the Medallion Architecture
• Re-cap of Dimensional Modelling
• Group Exercise: Designing the Analytical Data Model
Part 4. Data transformations
• Introduction to Spark and Notebook Engineering
• Hands-On Exercise: Moving Data Through the Medallion Layers
Part 5. Wrap up
• Architectural Considerations and Engineering Best Practices
• Recap and Key Takeaways