❓Are you wanting to get started with Fabric and want to know what all the parts are and do?
❓Have you been building data platforms for years and are looking to transition to Fabric?
This one-day collaborative workshop covers essential data engineering stages using Microsoft Fabric, incorporating practical experiences and best practices. The workshop is divided into key modules to help you leverage Microsoft Fabric for your data engineering projects.
Overview
1. Introduction to Microsoft Fabric
Get an overview of Microsoft Fabric, focusing on its capabilities for Data Engineering within Business Intelligence solutions. Explore Lakehouse architecture, SQL Endpoint, Data Warehouses, Data Virtualization, and Semantic Models.
2. Hands-on Experience with Ingestion and Modelling using Notebooks, Pipelines, and Dataflows
Participate in practical workshops to learn data ingestion and transformation techniques using Notebooks (Python, Spark, TSQL), Datafactory Pipelines, and Dataflows Gen 2. Understand the tools' pros and cons and when to use each.
3. Architecting Solutions
Learn to architect robust and scalable data engineering solutions using Fabric Artifacts. This module covers frameworks for data transformation stages such as ELT, including logging and metadata capturing.
4. Environment Management
Discover how to create efficient workspace architectures, design user access control, and monitor data engineering solutions. Implement best practices for efficient and reliable data processes.
5. Applying Your Skills
Apply the techniques learned to real-world scenarios, and by the end of the day, you will have created an end-to-end data engineering solution ready for self-service BI.
Format: The training includes lectures, hands-on activities, and group discussions for a comprehensive learning experience.

Data Transformation and Integration
Real-World Data Engineering: Practical Skills for Microsoft Fabric
Description
Learning Objectives
By the end of the day, attendees will have:
✅An understanding of Fabric Data Engineering Artifacts, which to chose and when
✅The ability to architect, develop and delivery data engineering solutions on Fabric
✅Frameworks for logging and metadata capturing
✅Practical skills ready to be applied to your projects
✅A Notebook Framework, tools, and references for architecting solutions in Microsoft Fabric
Things I will need
Tech Covered
Fabric, Data Transformation and Integration