DP-600: Microsoft Fabric Analytics Engineer
Course Overview
Course Description:
Become a key player in your organization’s data transformation journey by learning how to design, implement, and manage end-to-end analytics solutions with Microsoft Fabric. This instructor-led course equips you with the skills to work across the Microsoft data stack, including Power BI, Data Factory, Data Engineering, and Data Science workloads within Microsoft Fabric.
Through real-world scenarios and guided instruction, you'll master lakehouse architecture, build semantic models, perform data transformations, and deliver actionable insights using Power BI. Learn how to collaborate across business and technical teams to deliver unified, governed, and scalable data solutions that power decision-making.
This course includes 40%–50% hands-on activities, enabling you to apply your skills in a live Microsoft Fabric environment.
Target Audience:
This course is ideal for:
Analytics engineers, BI developers, and data professionals building analytics solutions using Microsoft Fabric
Power BI developers and data modelers who want to expand into full-stack Fabric analytics
Data engineers transitioning to unified analytics platforms
Professionals preparing for the Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) certification
Prerequisites:
Experience with data modeling, querying, and visualization. Familiarity with Power BI, SQL, and basic ETL/ELT concepts is recommended.
Course Outline:
Module 1: Introduction to Microsoft Fabric and Unified Analytics
Understand the architecture and components of Microsoft Fabric
Explore OneLake, lakehouse, data warehouse, and real-time analytics workloads
Identify key roles and responsibilities of a Fabric analytics engineer
Module 2: Ingest and Transform Data with Dataflows and Data Pipelines
Use Dataflows Gen2 to ingest, clean, and prepare data from various sources
Build scalable data pipelines with Data Factory in Microsoft Fabric
Implement ETL/ELT strategies and automate transformations using Spark notebooks and Data Wrangler
Module 3: Implement Lakehouse Architecture in Microsoft Fabric
Create and manage lakehouses using OneLake and Delta tables
Organize data in bronze, silver, and gold layers for analytic workloads
Integrate data from structured, semi-structured, and unstructured sources
Module 4: Design and Build Robust Semantic Models
Create star schemas and optimize Power BI semantic models
Define measures, hierarchies, and relationships using DAX and Power BI Desktop
Optimize performance with composite models, Direct Lake, and aggregation tables
Module 5: Deliver Data Insights with Power BI
Design interactive Power BI reports and dashboards using best practices
Integrate Power BI with Microsoft Fabric lakehouses for seamless data access
Configure row-level security (RLS), deployment pipelines, and data refresh
Module 6: Administer, Monitor, and Govern Fabric Analytics Solutions
Use workspace roles, sensitivity labels, and data lineage tools
Monitor datasets, pipelines, and usage with Fabric monitoring tools
Apply governance and compliance best practices across Fabric environments
Module 7: Enable Real-Time and Advanced Analytics
Work with KQL databases and event streaming data in Fabric
Implement real-time analytics dashboards with live data feeds
Explore integration with AI/ML models and advanced analytics using Notebooks
Delivery Format:
Instructor-led training with expert guidance
40%–50% hands-on learning in a live Microsoft Fabric environment
Practical exercises designed for real-world analytics engineering scenarios
Hands-On Labs
This course includes practical, hands-on laboratory exercises to reinforce your learning:
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