Want to learn Microsoft Fabric, here is a series of lessons that will help you to get started with Microsoft Fabric and its components.
- Lesson 1 – What is Microsoft Fabric and Fabric Terminologies?
- Lesson 2 – Microsoft Fabric Licensing Model
- Lesson 3 – Getting started with Microsoft Fabric
- Lesson 4 – Fabric Workspaces and how to create one?
- Lesson 5 – Workspace roles and access control
- Lesson 6 – What is Microsoft Fabric Lakehouse?
- Lesson 7 – Getting started with Microsoft Fabric Lakehouse
- Lesson 8 – Lakehouse architecture
- Lesson 9 – Shortcuts in a Lakehouse
- Lesson 10 – Ingest, transform, analyze and visualize data in a Lakehouse using Microsoft Fabric
- Lesson 11 – Ingest, transform, analyze and visualize data in a Lakehouse using Notebooks
- Lesson 12 – What is OneLake?
- Lesson 13 – Microsoft Fabric OneLake vs Lakehouse
- Lesson 14 – What is OneLake file explorer?
- Lesson 15 – Access data in OneLake using API
- Lesson 16 – Understanding OneLake Security
- Lesson 17 – What is OneLake Data Hub?
- Lesson 18 – Introduction to Data Pipelines in Microsoft Fabric
- Lesson 19 – Quick overview on Data Pipeline connectors
- Lesson 20 – Ingest data using Copy Activity in Microsoft Fabric
- Lesson 21 – What are Dataflows Gen2 in Microsoft Fabric?
- Lesson 22 – Quick overview on Dataflow Gen2 connectors
- Lesson 23 – Ingest data using Dataflows Gen2 in Microsoft Fabric
- Lesson 24 – Migration Path for Azure Data Factory to Microsoft Fabric
- Lesson 25 – Migration Path for Power BI Dataflow Gen1 to Dataflow Gen2 in Microsoft Fabric
- Lesson 26 – Upskill your Mapping Data flow transformation knowledge to Dataflow Gen2
- Lesson 27 – Using Notebooks with Microsoft Fabric
- Lesson 28 – Lifecycle management with Microsoft Fabric
- Lesson 29 – Microsoft Fabric and Git Integration
- Lesson 30 – Using Deployment Pipelines with Microsoft Fabric
- Lesson 31 – Lakehouse and Delta Tables
- Lesson 32 – Using SQL analytics endpoint with Lakehouse
- Lesson 33 – Using Power BI with Lakehouse
- Lesson 34 – Introduction to Data Science with Microsoft Fabric
- Lesson 35 – Creating a Machine Learning Model with Microsoft Fabric
- Lesson 36 – Data Wrangler in Microsoft Fabric
- Lesson 37 – Pre-Built AI Models in Microsoft Fabric
- Lesson 38 – Train Models with Spark Mlib with Microsoft Fabric
- Lesson 39 – Train Models with SynapseML
- Lesson 40 – Train models with Scikit-Learn
- Lesson 41 – Getting started with Apache Spark in Microsoft Fabric
- Lesson 42 – What is semantic link in Microsoft Fabric
- Lesson 43 – How to choose a data store in Microsoft Fabric?
- Lesson 44 – Load data into Warehouse in Microsoft Fabric (file upload, copy tool, copy activity, dataflow, Notebooks)
- Lesson 45 – Create Power BI Semantic Model from Warehouse in Microsoft Fabric
- Lesson 46 – How to apply row-level, column-level and dynamic data masking in Microsoft Fabric
- Lesson 47 – Manage and monitor performance of the Warehouse in Microsoft Fabric
- Lesson 48 – How to share a Warehouse using Microsoft Fabric?
- Lesson 49 – What is clone tables and how to do that using Fabric Portal?
- Lesson 50 – Cost savings with Fabric Data Warehousing
- Lesson 51 – Microsoft Fabric vs. Azure Synapse Analytics
- Lesson 52 – Microsoft Fabric vs. Azure Databricks
- Lesson 53 – Microsoft Fabric vs. Snowflake
- Lesson 54 – Migrate Synapse Dedicated SQL pool Warehouse to Microsoft Fabric
- Lesson 55 – Quick Introduction to Real-Time Analytics
- Lesson 56 – Real-Time Analytics vs. Azure Data Explorer
- Lesson 57 – Create and manage Event Streams with Microsoft Fabric
- Lesson 58 – Getting started with Kusto Query Language (KQL)
- Lesson 59 – Functions in KQL
- Lesson 60 – Visualize KQL Database data in Power BI
- Lesson 61 – Quick introduction to Data Activator
- Lesson 62 – Using Triggers with Data Activator
- Lesson 63 – Using Copilot in Microsoft Fabric
- Lesson 64 – Using SQL Projects for Warehouse in Microsoft Fabric