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DP-600: Microsoft Fabric Analytics Engineer Ultimate Course
Rating: 4.2 out of 5(24 ratings)
1,156 students

DP-600: Microsoft Fabric Analytics Engineer Ultimate Course

15+ REAL End-to-End Fabric Analytic Engineer Projects | 150+ High-Quality Practice Test Question with VIDEO Explanation!
Created byCloud Guru Amit
Last updated 5/2026
English

What you'll learn

  • Build hands-on solutions using Fabric Workspace, Lakehouse, and SQL Analytics Endpoints.
  • Design Fact & Dimension tables and create efficient Data Models for analytics.
  • Analyze performance using Dynamic Management Views (DMVs) and Query Insights.
  • Validate business data using Data Consistency checks in real-world scenarios.
  • Implement Dynamic Data Masking, Row-Level & Column-Level Security in Fabric.
  • Ingest and analyze real-time stock data using Eventstream and Eventhouse.
  • Train machine learning models on diabetic patient data for predictive insights.
  • Create advanced visualizations using Data Science Notebooks in Fabric.
  • Manage project tracking, issues, and dashboards with Fabric tools.
  • Develop CI/CD pipelines for continuous analytics deployment using Fabric.
  • Build and query APIs using GraphQL for real-time analytics and integration.
  • Implement Slowly Changing Dimensions (SCD) Type 1 and Type 2 in Lakehouse.
  • Configure Dynamic Data Masking in Azure SQL for sensitive data protection.
  • Create and manage Azure SQL Databases and Azure SQL Servers efficiently.
  • Query and visualize big data using Kusto Query Language in Azure Explorer.
  • Master SQL & Visual Query Editors to build and debug optimized queries.
  • Understand Delta Lake Tables and their role in transactional data lakes.
  • Work with PySpark DataFrames and Spark SQL to handle big data efficiently.
  • Distinguish between types of analytics and apply appropriate techniques.
  • Learn data warehousing principles and how Fabric fits into modern BI.
  • Master use of notebooks, dataframes, and scripting for analytics modeling.
  • Understand API architecture using GraphQL and implement it in Fabric.
  • Deep dive into theory behind SCDs and implement use cases in the cloud.
  • Practice with exam questions and understand Microsoft-backed answer logic.

Course content

5 sections • 122 lectures • 10h 9m total length

  • Workspace-Level Access Control0:58
  • Workspace-Level Access Control Hands on3:52
  • Item-Level Access Control1:07
  • Item-Level Access Control Hands on4:23
  • Row-level security1:02
  • Row-level Security Hands on6:17
  • Column-level security0:54
  • Object-level security1:01
  • File-Level Security0:56
  • File-Level Security Hands on4:35
  • File-Level Security Hands on4:35
  • Sensitivity labels1:17
  • Endorsements1:05
  • Endorsements Hands on2:02
  • Version Control in Workspaces1:03
  • Version Control in Workspaces Hands on10:41
  • Deployment pipelines1:17
  • Impact analysis of downstream dependencies1:05
  • Power BI templates (.pbit)1:09
  • Power BI templates (.pbit) Hands on2:23
  • Data source files (.pbids)1:05
  • Shared semantic models1:01

Requirements

  • Familiarity with basic SQL concepts like SELECT, JOIN, and WHERE clauses.
  • Awareness of data warehousing and analytics concepts.
  • Knowledge of Python basics
  • Prior exposure to Azure fundamentals

Description

Looking to ace the DP-600 exam and gain practical, real-world experience with Microsoft Fabric? This course offers a complete hands-on journey designed around projects that reflect real IT industry scenarios using Microsoft Fabric's modern analytics stack.

Each module begins with theory-first learning—covering essential concepts like Fabric Workspace, Lakehouse architecture, SQL Analytics Endpoints, Delta Tables, PySpark DataFrames, Spark SQL, Visual Query Editors, Eventhouses, SCD Types, and more. Then, you’ll dive into realistic, guided labs that strengthen technical skills while preparing you for certification success.


End-to-End Hands-on Projects Included:


  • Project #1: Fabric Workspace, Lakehouse & SQL Analytics Endpoint Setup

  • Project #2: Designing Fact Tables, Dimension Tables & Data Models

  • Project #3: Performance Tuning with Dynamic Management Views (DMV) & Query Insights

  • Project #4: Validating Data Consistency Across Sources

  • Project #5: Implementing Dynamic Data Masking in Azure SQL Database

  • Project #6: Securing Data with Row-Level & Column-Level Security in Fabric

  • Project #7: Real-Time Stock Data Ingestion & Analysis Using Eventstream

  • Project #8: Diabetic Patient Data Analysis & Predictive Model Training

  • Project #9: Data Science Notebook for Mastering Visualizations

  • Project #10: Building a Project Tracking & Issue Management System

  • Project #11: CI/CD Deployment Pipeline for Fabric Analytics Solutions

  • Project #12: Creating & Consuming an API with GraphQL

  • Project #13: SCD Type 1 & SCD Type 2 Implementation in Fabric

  • Project #14: Azure SQL Server & Database Configuration with Data Masking

  • Project #15: Azure Data Explorer – Kusto Query Language (KQL) Hands-on Demo

You’ll also gain access to interactive practice tests with detailed video explanations for both correct and incorrect choices—rooted in Microsoft documentation and explained using strategic elimination techniques.

This is not just another course—it’s your launchpad to becoming a confident, job-ready Fabric Analytics Engineer, taught by Cloud Guru Amit. Get certified, get skilled, and get ahead.

Who this course is for:

  • Aspiring Data Analysts, Engineers, and BI Developers looking to gain hands-on expertise with Microsoft Fabric and its analytics ecosystem.
  • IT professionals and database administrators seeking to upskill in Fabric Workspace, Lakehouse, and SQL Analytics Endpoints.
  • Candidates preparing for the DP-600 certification exam who want real-world, project-based learning to master the exam objectives.
  • Cloud and Data Engineers aiming to integrate Fabric tools with Azure services like Eventstream, SQL Database, and Data Explorer.
  • Developers and Architects interested in securing analytics solutions using Row-Level/Column-Level Security and Dynamic Data Masking.
  • Python or PySpark learners wanting to apply their skills in data science notebooks, model training, and data visualizations in Fabric.
  • Data-driven professionals who value understanding concepts deeply—like SCDs, DMVs, Delta Lake, GraphQL APIs—backed by hands-on execution.

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