DP-600: Microsoft Fabric Analytics Engineer

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