Want to learn Microsoft Fabric, here is a series of lessons that will help you to get started with Microsoft Fabric and its components.
Fabric Items Naming Conventions – Coming soon
- 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 Intelligence
- Lesson 56 – Real-Time Intelligence 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
- Lesson 65 – What is Fabric IQ? The Intelligent Layer of Microsoft Fabric
- Lesson 66 – Understanding the Fabric IQ Architecture
- Lesson 67 – Fabric IQ vs Traditional Semantic Models
- Lesson 68 – How Fabric IQ Enables AI Agents
- Lesson 69 – Creating your First Ontology in Microsoft Fabric (both using OneLake and Semantic Model)
- Lesson 70 – Understanding Ontology Concepts in Microsoft Fabric
- Lesson 71 – Creating Entity Types in Fabric Ontology
- Lesson 72 – Defining relationships in Fabric Ontology
- Lesson 73 – Binding Data Sources to Ontology
- Lesson 74 – Visualizing Data Relationships with Fabric Graph
- Lesson 75 – Introduction to Data Agents in Microsoft Fabric
- Lesson 76 – Creating a Data Agent in Microsoft Fabric
- Lesson 77 – Data Agents vs Copilot in Microsoft Fabric
- Lesson 78 – Operational Agents in Fabric IQ
- Lesson 79 – Monitoring Data Agents and Agent Governance
- Lesson 80 – How Copilot understands your Data using Semantic Models
- Lesson 81 – Natural Language Analytics with Copilot in Microsoft Fabric
- Lesson 82 – Databricks Genie vs. Copilot vs. Data Agents
- Lesson 83 – Direct Lake Architecture Explained
- Lesson 84 – Direct Lake vs. Import vs. Direct Query
- Lesson 85 – Direct Lake Internals – Query Execution
- Lesson 86 – Performance Optimization for Direct Lake
- Lesson 87 – Direct Lake Security
- Lesson 88 – Semantic Models in the Fabric Era
- Lesson 89 – Building Enterprise Semantic Models in Fabric
- Lesson 90 – DAX Query Performance in Fabric
- Lesson 91 – What is Mirroring in Microsoft Fabric
- Lesson 92 – Supported Sources for Fabric Mirroring
- Lesson 93 – Mirroring vs ETL Pipelines
- Lesson 94 – Mirroring with Azure SQL Database
- Lesson 95 – Mirroring with Azure SQL Managed Instance
- Lesson 96 – Mirroring with Azure Cosmos DB
- Lesson 97 – Mirroring with Azure Databricks
- Lesson 98 – Mirroring with Google BigQuery
- Lesson 99 – Mirroring with Oracle
- Lesson 100 – Mirroring with PostgreSQL
- Lesson 101 – Mirroring with SAP
- Lesson 102 – Mirroring with Snowflake
- Lesson 103 – Mirroring with SQL Server
- Lesson 104 – Implement Open Mirroring with MS Fabric
- Lesson 105 – Monitoring Mirrored Databases
- Lesson 106 – Introduction to Fabric Extensibility Toolkit
- Lesson 107 – Building Custom Fabric Workloads
- Lesson 108 – Consuming Custom Fabric Workloads
- Lesson 109 – Fabric APIs and Developer Integrations
- Lesson 110 – Automating Fabric Workflows with APIs
- Lesson 111 – Microsoft Fabric Tenant Administration
- Lesson 112 – Understanding Fabric Capacity Management
- Lesson 113 – Monitoring Fabric Capacity Usage
- Lesson 114 – Managing Fabric Workspaces at Scale
- Lesson 115 – Fabric Security Model for Administrators
- Lesson 116 – Auditing and Activity Logs in MS Fabric
- Lesson 117 – Governance Best Practices for MS Fabric
- Lesson 118 – Microsoft Purview Integration with MS Fabric
- Lesson 119 – Data Lineage in Microsoft Fabric
- Lesson 120 – Data Catalog and Discovery in Fabric
- Lesson 121 – Monitoring Fabric Workloads
- Lesson 122 – Query Performance Monitoring with MS Fabric
- Lesson 123 – Fabric Cost Optimization Strategies
- Lesson 124 – Troubleshooting Fabric Performance Issues
- Lesson 125 – Capacity Planning for Microsoft Fabric
- Lesson 126 – Integrating Microsoft Fabric with Azure Databricks
- Lesson 127 – Integrating MS Fabric with Azure AI Services
- Lesson 128 – Using MS Fabric with Azure Event Hubs
- Lesson 129 – Using MS Fabric with Azure Stream Analytics
- Lesson 130 – Integrating Fabric with Azure Machine Learning
- Lesson 131 – Implementing Medallion Architecture in Fabric
- Lesson 132 – Building Data Mesh with Microsoft Fabric
- Lesson 133 – Data Sharing across Domains with MS Fabric
- Lesson 134 – Designing Multi-Tenant Fabric Platforms
- Lesson 135 – CI/CD for Microsoft Fabric
- Lesson 136 – Automating Fabric Deployments
- Lesson 137 – Fabric Environment Promotion Strategies
- Lesson 138 – Version Control Best Practices in Fabric
- Lesson 139 – Testing strategies for Fabric Solutions