Microsoft Fabric: Lakehouse, Data Factory, Spark & SQL, Gen2

A practical Microsoft Fabric course covering OneLake, Lakehouse, Dataflow Gen2, Pipelines, Spark, PySpark, SQL Endpoints

What you’ll learn
Understand the complete architecture and core concepts of Microsoft Fabric.
Create and manage tenants, workspaces, capacities, and items in Fabric.
Work with OneLake, OneLake File Explorer, and Lakehouse storage architecture.
Design and manage Lakehouse tables and shortcuts (internal, external, caching).
Build and automate data pipelines using Microsoft Fabric Data Factory.
Use real-world pipeline activities such as Copy, Delete, Lookup, Filter, and Parameters.
Transform data using Dataflow Gen2 and Power Query transformations.
Process large-scale data using Apache Spark and PySpark in Microsoft Fabric.
Write and execute Spark SQL queries and perform data visualization in notebooks.
Monitor, schedule, and automate data workflows for production-ready solutions.

Requirements
Basic understanding of data concepts is helpful but not mandatory.
Familiarity with SQL or any programming language is a plus but not required.
Willingness to learn hands-on by following practical demonstrations.
No prior experience with Microsoft Fabric is required.

Description
This course is a complete, hands-on masterclass on Microsoft Fabric, designed to take you from absolute fundamentals to advanced, real-world data engineering workflows. It is built with a strong focus on practical implementation, not just theory, and follows a clear learn-by-doing approach throughout.Microsoft Fabric is Microsoft’s unified analytics platform, and mastering it requires a deep understanding of its architecture, storage layer, data ingestion tools, transformation capabilities, orchestration, monitoring, and large-scale processing engines. This course covers every major component of Microsoft Fabric in detail, ensuring you gain real production-level skills.You will begin by understanding the core foundation of Microsoft Fabric, including platform overview, account setup, tenants, workspaces, capacities, and item hierarchy. These concepts are explained clearly so you fully understand how Fabric operates at an organizational and enterprise level before moving into implementation.The course then moves into OneLake and Lakehouse architecture, where you learn how Microsoft Fabric unifies storage across analytics workloads. You will work with OneLake, OneLake File Explorer, create and manage Lakehouses, design tables, and implement shortcuts. Internal shortcuts, external shortcuts, and shortcut caching are covered in depth, giving you a strong understanding of data virtualization and storage optimization inside Fabric.A major strength of this course is its deep and practical coverage of Microsoft Fabric Data Factory. You will design pipelines step by step and work extensively with real pipeline activities used in production environments. This includes Copy Data, Delete, Get Metadata, Filter, Lookup, Parameters, ForEach, If Condition, Set Variable, Notification, Invoke Pipeline, and Wait activities. You will also learn how to schedule pipelines using triggers, automate workflows, and monitor pipeline runs, failures, and alerts. By the end of this section, you will be able to build fully automated and monitored data pipelines.The course also provides comprehensive training on Dataflow Gen2, focusing on data transformation using Power Query within Microsoft Fabric. You will work with string transformations, mathematical transformations, joins, diagram view, and loading transformed data into Lakehouse or Warehouse. This section bridges the gap between raw data ingestion and analytics-ready datasets.On the processing and analytics side, the course delivers in-depth coverage of Apache Spark in Microsoft Fabric. You will work with Spark pools and Spark notebooks and gain strong hands-on experience with PySpark. Topics include DataFrame creation, column selection and removal, filtering, sorting, grouping, handling null values, type casting, column transformations, Spark SQL, and data visualization within notebooks. These lessons prepare you to process large-scale data efficiently using Spark inside Microsoft Fabric.Throughout the course, special attention is given to monitoring, reliability, and automation, ensuring you understand how to track executions, handle failures, and maintain scalable, production-ready solutions.By the end of this course, you will have end-to-end practical expertise in building, transforming, orchestrating, and monitoring modern data engineering solutions using Microsoft Fabric.What This Course Covers (Content Highlights)Microsoft Fabric architecture, hierarchy, tenants, workspaces, capacities, and itemsOneLake fundamentals, OneLake File Explorer, and data organizationLakehouse concepts, creation, table design, and managementShortcuts in Fabric: internal, external, and caching strategiesSQL Endpoints and querying data in Microsoft FabricData Factory pipelines with real-world activities and automationPipeline scheduling, triggers, monitoring, failures, and alertsDataflow Gen2 with Power Query transformations and data loadingApache Spark in Microsoft Fabric with Spark pools and notebooksPySpark fundamentals and advanced transformationsSpark SQL and data visualization in notebooksEnd-to-end monitoring, automation, and best practicesWho This Course Is ForThis course is ideal for aspiring data engineers, BI professionals, developers, and analytics engineers who want practical, real-world expertise in Microsoft Fabric. It is suitable for beginners who want a complete learning path as well as professionals who want to strengthen their Fabric and modern data engineering skills.

Who this course is for
Beginners who want to learn Microsoft Fabric from scratch.
Aspiring data engineers looking to build modern data platforms.
BI professionals who want to work with Lakehouse and OneLake architecture.
Developers who want hands-on experience with Data Factory, Spark, and PySpark.
Professionals who want practical, end-to-end Microsoft Fabric skills for real-world projects.