Microsoft Fabric Training
Master End-to-End Data Engineering, Analytics & Business Intelligence
Build practical, job-ready Microsoft Fabric skills from fundamentals to advanced implementation. Learn OneLake, Lakehouse, Data Factory, Apache Spark, Data Warehouse, Real-Time Intelligence, Power BI, semantic models, governance, security, performance optimization and production analytics solutions.
Enquire About TrainingCourse Overview
Microsoft Fabric is a unified SaaS analytics platform that brings together data integration, data engineering, data warehousing, data science, real-time intelligence and Power BI on a shared data foundation called OneLake. This training takes you from Fabric fundamentals to advanced, practical end-to-end implementation.
You will create Fabric workspaces and lakehouses, ingest data with Data Factory, transform data using Spark and notebooks, work with Delta Lake tables, build warehouses and SQL solutions, develop semantic models and Power BI reports, process real-time data, and implement security, governance, monitoring, performance and deployment practices.
Course Highlights
Learn the major Microsoft Fabric workloads through practical exercises and end-to-end scenarios, moving from cloud data fundamentals to production-ready analytics architecture.
Fabric Architecture
Understand Fabric workloads, workspaces, items, capacities, OneLake and how the platform connects the complete data lifecycle.
OneLake & Lakehouse
Build lakehouses, work with files and Delta tables, use shortcuts and understand the unified storage model across Fabric workloads.
Data Factory
Build ingestion and orchestration solutions using Copy jobs, pipelines, Dataflow Gen2, connectors, parameters, triggers and monitoring.
Spark & Data Engineering
Use notebooks, Apache Spark, PySpark, DataFrames and Spark jobs to build scalable transformation and data engineering workflows.
Fabric Data Warehouse
Develop SQL-based warehouse solutions, dimensional models, views, procedures, loading patterns, performance strategies and reporting datasets.
Power BI & Semantic Models
Build semantic models, DAX measures and Power BI reports using Fabric data, including Direct Lake concepts and governed analytics.
Real-Time Intelligence
Work with Real-Time hub, Eventstreams, Eventhouse, KQL and real-time dashboards for streaming and event-driven scenarios.
Security & Governance
Understand workspace roles, item permissions, Microsoft Purview concepts, sensitivity, lineage, governance and secure enterprise access.
Why Choose Our Microsoft Fabric Training?
The training is designed around practical implementation rather than isolated product features, connecting ingestion, engineering, warehousing, analytics, real-time processing and reporting.
End-to-End Data Platform
Follow data from source systems through ingestion, OneLake, transformation, warehouse or lakehouse, semantic models and Power BI.
SQL + PySpark
Develop solutions using SQL, notebooks, Python and PySpark so you can work across engineering and analytics workloads.
Practical ETL & ELT
Build reusable ingestion and transformation workflows with Data Factory, pipelines, Dataflow Gen2, notebooks and SQL.
Analytics-Ready Modeling
Learn dimensional modeling, semantic models, DAX and reporting patterns that turn engineered data into business insights.
Batch & Real-Time
Understand both traditional batch data pipelines and streaming/event-driven analytics with Fabric Real-Time Intelligence.
Production Practices
Apply Git, deployment, monitoring, capacity awareness, security, governance, performance tuning and operational best practices.
Who Can Join?
Freshers & Graduates
Students and graduates who want to build careers in cloud data engineering, analytics and Microsoft data platforms.
SQL & Database Professionals
SQL developers and database professionals who want to move into modern cloud data engineering, warehousing and analytics.
ETL & Data Engineers
ETL developers and data engineers who want practical OneLake, Lakehouse, Spark, pipelines and Fabric architecture skills.
Analytics Professionals
Power BI and analytics professionals who want to understand the engineering, warehousing and semantic-model layers behind analytics.
Azure Professionals
Azure professionals who want to add Microsoft's unified SaaS analytics platform to their cloud data skill set.
Developers & Technical Teams
Developers and technical professionals who want hands-on experience building complete Fabric data solutions.
Career Opportunities
Microsoft Fabric Data Engineer
Design ingestion, transformation, lakehouse and orchestration solutions using Fabric data engineering capabilities.
Cloud Data Engineer
Build modern cloud data platforms using OneLake, Spark, pipelines, SQL and integrated analytics workloads.
Data Warehouse Developer
Develop SQL warehouse solutions, dimensional models and analytics-ready data structures in Fabric.
Fabric Analytics Engineer
Connect engineered data to semantic models, DAX and Power BI for governed business analytics.
Real-Time Analytics Developer
Build streaming and event-driven analytics solutions using Real-Time hub, Eventstreams, Eventhouse and KQL.
Data Platform Specialist
Work across Fabric architecture, governance, security, monitoring, deployment and enterprise data-platform operations.
What You Will Gain
Fabric Platform Skills
Understand Fabric architecture, workloads, workspaces, capacities, OneLake and the unified analytics environment.
Lakehouse Engineering
Build lakehouse solutions using files, Delta tables, notebooks, Spark and practical medallion-style data flows.
Data Integration
Build reliable ingestion and orchestration workflows using Fabric Data Factory capabilities.
Warehouse & SQL
Develop SQL warehouse solutions and analytical models suitable for reporting and business intelligence.
Power BI Analytics
Build semantic models, measures and reports on Fabric data using modern Power BI integration patterns.
Governed Production Solutions
Apply security, governance, monitoring, performance, deployment and operational practices to real-world solutions.
Trusted Microsoft Fabric Training
Learn from an experienced training institute with a practical, technology-focused approach to professional training.
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Upcoming Free Demo Class
📚 Course: Microsoft Fabric Training
📅 Start Date: 16 October 2026
🕒 Time: 09:00 PM - 10:00 PM IST
⏰ Class: 1 Hour
🗓️ Schedule: Weekdays-Online
⌛ Duration: 8 Weeks
💰 Course Fee: Contact us for Fee Details
🌐 Meeting Link: Contact us for zoom meeting link
Live Microsoft Fabric Training Sessions
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Course Syllabus
01. Microsoft Fabric Fundamentals & Architecture
FOUNDATION
- What is Microsoft Fabric?
- Microsoft Fabric SaaS architecture
- Fabric workloads and experiences
- Data Engineering, Data Factory and Data Warehouse
- Data Science, Real-Time Intelligence and Power BI
- Fabric workspaces, items and capacities
- OneLake as the unified logical data lake
- Fabric lakehouse architecture
- Fabric user roles and development workflow
- End-to-end Fabric analytics architecture
02. OneLake, Workspaces & Lakehouse
STORAGE & DATA FOUNDATION
- Create and manage Fabric workspaces
- Lakehouse architecture and components
- Files and Tables areas
- Delta Lake and table concepts
- Structured and unstructured data
- Loading files into OneLake
- Lakehouse tables and schemas
- OneLake shortcuts and external data access
- Medallion architecture: Bronze, Silver and Gold
- Practical lakehouse project
03. Fabric Data Factory & Data Ingestion
DATA INTEGRATION
- Fabric Data Factory overview
- Connecting databases, files, APIs and cloud sources
- Connectors and gateways
- Copy job fundamentals
- Bulk and incremental ingestion
- Change data capture concepts
- Fabric pipelines
- Linked connections and reusable parameters
- Pipeline activities and control flow
- Monitoring ingestion and troubleshooting failures
04. Dataflow Gen2, Power Query & Transformation
ETL & ELT
- Dataflow Gen2 architecture
- Power Query in Fabric
- Connecting and profiling source data
- Filtering, cleansing and standardizing data
- Joins, merges, aggregations and derived columns
- Reusable transformation logic
- Parameters and dynamic dataflows
- Loading transformed data into Fabric destinations
- Choosing pipelines, Copy jobs, Dataflow Gen2 or notebooks
- Practical ETL/ELT project
05. Apache Spark, Notebooks & PySpark
DATA ENGINEERING
- Fabric Spark architecture
- Creating and using notebooks
- PySpark fundamentals
- DataFrames and Spark SQL
- Reading and writing Lakehouse data
- Data cleansing and transformation with PySpark
- Joins, aggregations and window functions
- Delta table operations
- Spark job definitions
- Scheduling and orchestrating notebooks and Spark jobs
06. Fabric Data Warehouse & SQL Development
DATA WAREHOUSING
- Fabric Data Warehouse architecture
- Creating warehouse objects
- T-SQL development
- Tables, views and stored procedures
- Data loading and transformation patterns
- Fact and dimension tables
- Star schema and dimensional modeling
- Warehouse and Lakehouse comparison
- Query performance considerations
- Building an analytical warehouse project
07. Semantic Models, DAX & Power BI in Fabric
ANALYTICS & BUSINESS INTELLIGENCE
- Power BI experience inside Fabric
- Creating semantic models
- Dimensional model relationships
- Measures and calculated columns
- DAX fundamentals and advanced measures
- Filter context and evaluation concepts
- Direct Lake concepts
- Report and dashboard development
- Semantic model security and governance
- End-to-end Fabric analytics project
08. Real-Time Intelligence, Eventstreams & KQL
REAL-TIME ANALYTICS
- Real-Time Intelligence architecture
- Real-Time hub
- Eventstreams and event-driven ingestion
- Eventhouse and KQL databases
- Kusto Query Language fundamentals
- Streaming data transformations
- Real-time dashboards and visualizations
- Alerts and event-driven actions
- Integration with OneLake and Power BI
- Practical streaming analytics scenario
09. Fabric Data Science, ML & AI Integration
DATA SCIENCE
- Fabric Data Science overview
- Data science notebooks
- Data preparation with Spark and Python
- Feature engineering concepts
- Machine learning experiments
- MLflow experiment tracking concepts
- Model registration and lifecycle concepts
- Batch scoring and prediction results
- Writing predictions back to the Lakehouse
- Visualizing ML results with Power BI
10. Performance, Capacity & Cost Optimization
OPTIMIZATION
- Fabric capacity fundamentals
- Understanding workloads and capacity consumption
- Lakehouse and Delta performance considerations
- SQL query optimization
- Spark performance fundamentals
- Pipeline and Dataflow optimization
- Power BI semantic model performance
- Monitoring capacity usage
- Workload management considerations
- Cost-aware architecture design
11. Security, Governance, Lineage & Administration
SECURITY & GOVERNANCE
- Fabric workspace roles
- Item permissions and access control
- Microsoft Entra identity concepts
- OneLake security concepts
- Data governance fundamentals
- Microsoft Purview integration concepts
- Data discovery and OneLake Catalog
- Lineage and impact analysis
- Sensitivity labels and compliance concepts
- Enterprise governance practices
12. Git, Deployment & CI/CD
DEVOPS & LIFECYCLE MANAGEMENT
- Git integration with Fabric workspaces
- Source control and collaboration
- Development, test and production environments
- Deployment pipelines
- Environment-specific configuration
- Release management
- Automated deployment concepts
- Monitoring deployment issues
- Reusable project structures
- Production release best practices
13. Advanced Microsoft Fabric Architecture & End-to-End Project
ADVANCED PRACTICAL IMPLEMENTATION
- Enterprise Microsoft Fabric architecture
- OneLake-centered data platform design
- Lakehouse vs Warehouse workload decisions
- Batch and real-time architecture patterns
- Metadata-driven ingestion concepts
- Reusable engineering and analytics frameworks
- Security and governance architecture
- Capacity, performance and cost strategy
- Production monitoring and operational readiness
- End-to-end project: source systems → Fabric Data Factory → OneLake/Lakehouse → Spark/SQL → Warehouse → Semantic Model → Power BI
- Advanced real-world troubleshooting and architecture scenarios
Sample Microsoft Fabric Training Videos
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Frequently Asked Questions
What is Microsoft Fabric?
Microsoft Fabric is a unified SaaS analytics platform that brings together data integration, data engineering, data warehousing, data science, real-time intelligence and Power BI on a shared data foundation called OneLake.
Is Microsoft Fabric suitable for data engineering?
Yes. Fabric provides Data Engineering capabilities based on Apache Spark, notebooks, lakehouses, pipelines and data transformation workflows for collecting, storing, processing and analyzing large volumes of data.
Will OneLake and Lakehouse be covered?
Yes. The course covers OneLake, workspaces, Lakehouse architecture, files, Delta tables, shortcuts, medallion-style data flows and practical data engineering scenarios.
Will Fabric Data Factory be covered?
Yes. The training covers Copy jobs, pipelines, connectors, Dataflow Gen2, orchestration, parameters, transformations, monitoring and practical ETL/ELT scenarios.
Will Apache Spark and PySpark be covered?
Yes. You will work with Fabric notebooks, Spark, PySpark, DataFrames, Spark SQL, Delta tables and Spark-based transformation workflows.
Will Power BI be part of the Microsoft Fabric training?
Yes. The course includes semantic models, DAX, Power BI reporting and Fabric analytics integration so that engineered data can be consumed as governed business intelligence.
Will Real-Time Intelligence be covered?
Yes. The curriculum includes Real-Time hub, Eventstreams, Eventhouse, KQL, streaming data and real-time analytics scenarios.
Will security, governance and deployment be covered?
Yes. The advanced modules cover workspace security, governance, lineage, Microsoft Purview concepts, Git, deployment pipelines, monitoring, capacity and production practices.
Is this training suitable for beginners?
Yes. The curriculum starts with Microsoft Fabric fundamentals and progressively moves into Lakehouse, Data Factory, Spark, Warehouse, Power BI, Real-Time Intelligence and advanced production architecture.
Ready to Learn Microsoft Fabric?
Learn Microsoft Fabric step by step and build complete modern data solutions using OneLake, Lakehouse, Data Factory, Spark, Data Warehouse, Real-Time Intelligence and Power BI.
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