Master the most powerful end-to-end data platform from Microsoft that unites data engineering, data science, real-time analytics, and business intelligence in one place.
This is not just another data course — it’s a career accelerator. Learn to work with Lakehouses, Notebooks, Power BI, Pipelines, Real-Time Data, and AI in one unified ecosystem.
Microsoft Fabric is the future of data architecture and analytics, designed to replace disconnected tools with a single SaaS-based data platform. Whether you’re a BI expert, data engineer, analyst, or decision-maker, Fabric allows you to build complete data solutions without switching tools.
This course is ideal for:
✅ Data Engineers and Analysts
✅ Power BI Developers upgrading to Fabric
✅ BI Consultants and Solution Architects
✅ AI and ML Engineers
✅ Business and IT Professionals
✅ Students pursuing data careers
✅ Freelancers and agency-based consultants
✅ Complete Microsoft Fabric Ecosystem
✅ Lakehouse and Data Engineering
✅ Real-Time Analytics with KQL
✅ Data Science Notebooks and Models
✅ Power BI Integration and Governance
✅ Git and CI/CD for Fabric
✅ Fabric Administration and Security
✅ Real-world Projects for Job Readiness
✅ 12 Industry-Focused Modules
✅ 6 Hands-On Projects
✅ Real-Time Analytics & ML Practice
✅ Access to Private Community & Mentorship
✅ Certificate of Completion
✅ Job Prep Kit + Interview Support
Rukhsar Nadeem
Data Engineer
Arham Matloob
BI Developer
Inam ul Haq
Big Data Consultant
Saqib Lateef
BI Developer
Jawad Riaz
BI Developer
Saad Farooq
Laravel Developer
What is Microsoft Fabric?
SaaS-Based Unified Platform Explained
Fabric Architecture & Real-World Use Cases
Difference Between Fabric vs Traditional Data Stack
Licensing Models (Free, Pro, PPU, Capacity)
Creating a Lakehouse in Fabric
Importing Data from SQL, Blob, APIs
Managing Delta Tables
Spark & PySpark Basics for Fabric
Developing ETL Pipelines with Lakehouse
Creating and Managing Warehouses
SQL Endpoints and T-SQL Queries
Designing Star Schema in Fabric Warehouse
Performance Tips & Indexing
Creating Reports from Lakehouse/Warehouse
Direct Lake vs Import vs DirectQuery
Building Unified Datasets in Fabric
Semantic Models & DAX Integration
Publishing, Sharing & Governance
Workspace & Capacity Management
Security Roles, Row-Level Security
Data Lineage and Microsoft Purview Integration
Audit Logs and Usage Analytics
Environment Setup for Enterprises
Introduction to OneLake
Lakehouse vs Warehouse Concepts
Delta Lake Format & Tables
Data Zones (Raw, Curated, Gold)
Mounting External Storage
Understanding Data Factory in Fabric
Building Pipelines for ETL/ELT
Dataflows Gen2 vs Pipelines
Triggers, Schedules, Activities
Parameterization and Reusability
Intro to KQL (Kusto Query Language)
Creating KQL Databases & Tables
Ingesting Streaming Data
Dashboards on Real-Time Feeds
Integrating with Azure Event Hubs
Python & Spark Notebooks in Fabric
ML Models in Fabric Environment
Data Exploration & Feature Engineering
Integration with Lakehouse Tables
MLOps Readiness in Fabric
**Module 10: DevOps, Git & CI/CD**
– Connecting Git Repos to Fabric
– Version Control for Pipelines, Reports & Notebooks
– Deployment Pipelines for Fabric
– Dev, Test, Prod Workspaces
– Release Management Best Practices
**Module 11: Advanced Topics**
– Performance Optimization in Lakehouse
– Data Quality, Metadata, and Schema Evolution
– Custom Connectors & External APIs
– Cost Optimization & Monitoring
– Delta Live Tables (Advanced)
– Unified Datasets & Semantic Layer Best Practices
– AI Visuals and Copilot Integration
**Module 12: Capstone Projects & Job Prep**
– Sales Analytics Lakehouse
– IoT Real-Time Streaming
– Marketing Attribution with Notebooks
– ML Forecasting Model
– Unified Power BI Dashboard from Warehouse
– Mock Interviews & Resume Optimization
– Career Guidance & Freelancing Tips
