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The Microsoft Fabric Training Syllabus provides a comprehensive learning path covering data engineering, data science, real-time analytics, Power BI integration, and AI workloads on a unified analytics platform. It explains how Microsoft Fabric brings together data movement, processing, visualization, and advanced analytics in one ecosystem. This syllabus is important as it helps professionals build end-to-end analytics solutions with practical, project-based experience. It is ideal for data engineers, data analysts, BI developers, data scientists, cloud professionals, and freshers looking to work on modern Microsoft analytics technologies.

Duration of Training : 50 Hours
Batch type : Weekdays/Weekends
Mode of Training : Classroom/Online/Corporate Training
Detailed Syllabus • Hands-on Labs • Assignments • Projects

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Overview

The Syllabus

Curriculum Designed by Experts

Module 1: Introduction to Microsoft Fabric (2 Hours)

• Overview of Microsoft Fabric Platform
• Understanding Unified Data Architecture: OneLake, OneCopy, OneSecurity
• Components of Microsoft Fabric:
o Data Factory
o Data Engineering
o Data Science
o Data Warehouse
o Real-Time Analytics
o Power BI
• Comparison with Azure Synapse and Power BI Ecosystem
• Role of Microsoft Fabric in Modern Data Analytics
Assignment:
• Explore Microsoft Fabric portal and identify core components.

Module 2: Understanding OneLake and Data Architecture (3 Hours)

• What is OneLake and How It Works
• Connecting Fabric to Azure Data Sources (Blob, SQL, Datalake Gen2)
• Security & Governance in OneLake
• Creating Workspaces and Managing Data Access
• Data Sharing and Collaboration Across Teams
Assignment:
• Create a new workspace and connect a OneLake data source.
Project Scenario:
• Set up a secure workspace for data engineering and analytics teams.

Module 3: Microsoft Fabric Data Engineering (6 Hours)

• Creating and Managing Lakehouses
• Data Ingestion using Dataflows and Pipelines
• Data Transformation using PySpark and Notebooks
• Scheduling and Orchestrating Pipelines
• Working with Delta Tables and Data Versioning
Assignment:
• Build a pipeline to ingest CSV and JSON data into a Lakehouse.
Project Scenario:
• Design and automate a daily ETL pipeline that transforms raw sales data into curated analytics data.

Module 4: Microsoft Fabric Data Factory (4 Hours)

• Overview of Fabric Data Factory
• Pipelines vs Dataflows
• Data Movement using Copy Activity
• Transformations using Mapping Dataflows
• Integration with Azure Data Services and On-Premise Systems
Assignment:
• Create and schedule a pipeline to copy data from SQL Server to OneLake.
Project Scenario:
• Automate monthly financial data ingestion with Fabric Data Factory and
monitoring alerts.

Module 5: Microsoft Fabric Data Warehouse (5 Hours)

• Introduction to Fabric Warehouse (SQL Endpoint)
• Creating Fact and Dimension Tables
• Querying Data using T-SQL
• Performance Optimization and Caching
• Integration with Power BI and Reporting Layers
Assignment:
• Create a data warehouse with sales and customer dimension tables.
Project Scenario:
• Develop an end-to-end data warehouse to support sales forecasting
dashboards.

Module 6: Microsoft Fabric Data Science (5 Hours)

• Overview of Data Science in Fabric
• Using Notebooks for Data Exploration (Python, R)
• Feature Engineering & Model Training with MLflow
• Integrating Azure Machine Learning in Fabric
• Deploying Models and Using Predictions in Power BI
Assignment:
• Build and deploy a simple regression model predicting sales using Fabric
Notebook.
Project Scenario:
• Train and deploy a customer churn prediction model using Fabric’s ML
environment.

Module 7: Real-Time Analytics in Microsoft Fabric (4 Hours)

• Introduction to KQL (Kusto Query Language)
• Setting Up Real-Time Data Streams
• Ingesting Streaming Data from IoT / Event Hubs
• Real-Time Dashboards in Power BI
• Monitoring Fabric Streaming Jobs
Assignment:
• Create a KQL database and analyze streaming sensor data.
Project Scenario:
• Design a live operations dashboard for tracking IoT sensor metrics in real-time.

Module 8: Power BI Integration with Microsoft Fabric (6 Hours)

• Connecting Power BI to OneLake and Lakehouse
• Data Modeling and DAX Calculations
• Building Interactive Reports & Dashboards
• Using Power BI Service with Fabric for Collaboration
• Power BI Dataflows and Dataset Refresh Automation
Assignment:
• Build a Power BI dashboard connected to Fabric Lakehouse data.
Project Scenario:
• Create a Fabric-integrated Power BI dashboard showing sales KPIs with DAX metrics.

Module 9: Governance, Security, and Administration (3 Hours)

• Access Control and Row-Level Security
• Data Sensitivity Labels and Encryption
• Monitoring Workspaces and Pipelines
• Backup, Versioning, and Disaster Recovery
• Cost Optimization and Billing in Microsoft Fabric
Assignment:
• Configure access permissions for multiple roles in Fabric workspace.

Module 10: End-to-End Fabric Project (6–8 Hours)

Project 1: Enterprise Data Analytics Platform (End-to-End)
Objective: Build a unified analytics platform using Fabric.
Steps:
• Ingest sales and customer data via Data Factory.
• Store in Lakehouse and transform using Data Engineering.
• Create a Data Warehouse schema.
• Build dashboards in Power BI integrated with Fabric datasets.
Deliverable: An end-to-end business analytics dashboard with Fabric
integration.
Project 2: Real-Time Analytics Dashboard
Objective: Stream IoT or stock data using Fabric Real-Time Analytics and visualize with Power BI.
Project 3: Predictive Analytics Model
Objective: Build and deploy an ML model using Fabric Data Science and connect results to dashboards.

Duration: 40–50 Hours

Module	Hours
Overview & Architecture	5
Data Engineering & Factory	10
Data Warehouse	5
Data Science & Real-Time Analytics	9
Power BI & Governance	7
Projects & Assignments	8–10

Tools & Technologies Covered

• Microsoft Fabric Platform
• OneLake / Lakehouse / Data Warehouse
• Power BI (Desktop & Service)
• Data Factory & Pipelines
• KQL (Kusto Query Language)
• Python / PySpark / MLflow
• Azure Synapse / Dataflows Integration

Learning Outcomes

After completing this training, learners will be able to:
✅ Build, manage, and automate end-to-end data pipelines in Microsoft Fabric.
✅ Integrate real-time, batch, and AI-driven analytics in a unified workspace.
✅ Design Data Warehouses and Lakehouses with Power BI reporting.
✅ Apply machine learning models within Fabric workflows.
✅ Develop enterprise-grade Fabric projects integrating governance and security.

Job-Oriented Roles

• Microsoft Fabric Data Engineer
• Power BI & Fabric Developer
• Data Analyst / BI Specialist
• Data Architect (Fabric & Azure Ecosystem)
• Data Science Engineer

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Microsoft Fabric Course Certification With Training In Bangalore

Q: Module 10: End-to-End Fabric Project (6–8 Hours)

Project 1: Enterprise Data Analytics Platform (End-to-End) Objective: Build a unified analytics platform using Fabric. Steps: • Ingest sales and customer data via Data Factory. • Store in Lakehouse and transform using Data Engineering. • Create a Data Warehouse schema. • Build dashboards in Power BI integrated with Fabric datasets. Deliverable: An end-to-end business analytics dashboard with Fabric integration. Project 2: Real-Time Analytics Dashboard Objective: Stream IoT or stock data using Fabric Real-Time Analytics and visualize with Power BI. Project 3: Predictive Analytics Model Objective: Build and deploy an ML model using Fabric Data Science and connect results to dashboards.

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