Microsoft Fabric

Overview

Microsoft Fabric is an end-to-end analytics platform that unifies data engineering, data science, real-time analytics, and business intelligence in a single SaaS solution. It brings together services like Data Factory, Synapse Data Engineering, Synapse Data Warehousing, and Power BI under one integrated environment. The platform allows teams to connect and manage diverse data sources, transform and store data in a unified OneLake, and deliver actionable insights with advanced analytics and reporting.

This course is designed to help learners understand the core components, architecture, and hands-on capabilities of Microsoft Fabric. You will explore features such as lakehouses, data pipelines, notebooks, warehousing, and AI-powered analytics, while also learning security, governance, and workspace management. By the end of the course, you will be able to build complete data solutions—from ingestion to visualization—making you job-ready for roles in data engineering, BI development, and cloud analytics.

Key Features

  • OneLake – Unified Data Lake : A single, centralized storage layer for all analytics workloads across the organization.
  • End-to-End Analytics Platform : Combines data integration, engineering, warehousing, real-time analytics, data science, and BI in one solution.
  • Integrated Power BI : Native visualization and reporting tools for faster, insight-driven decision-making.
  • Data Factory Integration : Build and manage pipelines for data ingestion, transformation, and orchestration.
  • Lakehouse & Warehouse Support : Uses both file-based and SQL-based data architectures for flexible analytics needs.
  • Real-Time Analytics : Process streaming and event-driven data for instant insights.
  • AI & Machine Learning Capabilities : Built-in notebooks, predictive analytics, and support for models trained with Azure Machine Learning.
  • Unified Security & Governance : Centralized access control, data lineage, and compliance features across all workloads.
  • Low-Code / No-Code Development : Easy data workflows and analytics capabilities for analysts and business users.
  • SaaS-Based Simplicity : Fully managed cloud platform—no need for complex infrastructure setup or maintenance.

Course Objectives

  • Understand Microsoft Fabric Architecture
  • Ingest and Manage Data Efficiently
  • Develop Analytics Workloads
  • Implement Data Engineering Practices
  • Design Real-Time Data Solutions
  • Apply AI & Machine Learning Capabilities
  • Build Interactive Dashboards and Reports
  • Ensure Security, Governance & Compliance
  • Deploy End-to-End Analytical Solutions

Job Opportunities After Completing the course

  • Data Engineer
  • Business Intelligence (BI) Developer
  • Data Analyst / Business Analyst
  • Data Architect
  • Analytics Engineer
  • Cloud Data Engineer
  • Power BI Developer
  • Azure Data Engineer
  • Data Platform Administrator

Salary Prospects

Country
Average Salary
United States
$70,000 to $130,000 per year
United Kingdom
£40,000 to £80,000 per year
India
INR 3 lakh to INR 25 lakh per year
Australia
AUD 70,000 to AUD 140,000
UAE
AED 90,000 to AED 600,000 per year
Singapore
SGD 50,000 toSGD 180,000 per year

Who should take CyberArk Training Courses?

  • Data Engineers
  • Power BI Developers & BI Professionals
  • Data Analysts / Business Analysts
  • Azure Data Engineers
  • Cloud & Data Architects
  • IT & Database Administrators
  • AI/ML Engineers
  • Students & Freshers

Course Content

  • What is Microsoft Fabric?
  • Why Microsoft Fabric? (Unified Lakehouse Architecture)
  • Key Components of Fabric
    o OneLake
    o Lakehouse
    o Warehouse
    o Data Engineering
    o Data Science
    o Real-Time Analytics
    o Power BI
  • Fabric vs Azure Synapse vs Databricks
  • What is OneLake?
  • Delta Lake & Parquet Concepts
  • Workspaces, Lakehouses & Files
  • Data Ingestion Methods into OneLake
  • Introduction to Fabric Notebooks (PySpark / SQL)
  • Lakehouse Explorer Overview
  • Create & Manage Tables (Managed & External Tables)
  • Data Wrangling & Transformation using PySpark
  • Scheduling & Pipeline Automation
  • Data Pipelines in Fabric
  • Copy Data Activity (Source → Destination)
  • Link & Access On-Prem & Cloud Data Sources
  • Dataflows Gen1 vs Gen2
  • Slowly Changing Dimensions (SCD Type 1 & Type 2)
  • Fabric SQL Warehouse Overview
  • Designing Star & Snowflake Schemas
  • Dimensional Data Modeling
  • SQL Stored Procedures, Views & UDFs
  • DW Performance Tuning & Indexing
  • KQL (Kusto Query Language) Basics
  • Streaming Data Sources (Kafka / Event Hub / IoT Hub)
  • Ingest Real-Time Data into Fabric
  • Materialized Views
  • Real-Time Operational Analytics Dashboards
  • Data Science Workspace Overview
  • ML Model Training using Notebooks (PySpark / Python)
  • Using AutoML in Fabric
  • Deploy & Consume Models in Analytics Workflows
  • Integration with Azure AI & OpenAI

Power BI Desktop & Fabric Model Architecture
• Direct Lake vs Import vs Direct Query
• Create Reports & Dashboards
• Row-Level Security (RLS)
• Publish & Govern Reports in Fabric

  • Fabric Security Model (Workspace, Item & Row-Level)
  • Data Lineage & Data Catalog
  • Cost Optimization
  • Logging & Monitoring
  • Source Control Integration (Git Repo)
  • CI/CD for Power BI, Lakehouse & Warehouse
  • Version Control Best Practices

Are you ready to take your career to the next level and become a cyber security expert?

Enroll in our course today and take the first step towards your career success!

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