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DP-600 Microsoft Fabric Analytics Engineer

Modern analytics platforms bring ingestion, modeling, and reporting together in a seamless workflow. Microsoft Fabric provides the technical foundation – scalable, governance-ready, and tightly integrated with existing business intelligence tools.

Key topics

  • Build data pipelines from source to report with Microsoft Fabric.
  • Deploy lakehouse architectures as the core analytical foundation.
  • Design semantic models and data structures for analytical workloads.
  • Automate workflows and implement orchestration logic.
  • Apply access controls, compliance measures, and governance concepts.
  • Connect and integrate reporting and analytics layers seamlessly.

Prerequisite
Participants with experience in SQL, BI, or cloud environments can jump straight into the content – familiarity with data structures and analytics workflows is beneficial.

Target group
Teams and individuals responsible for modeling, pipelines, or reporting in data-intensive projects.

Those who view data as a strategic resource will benefit from a course that sharpens both technical know-how and architectural thinking.

Course content
  • Understanding the structure and behavior of Gen2 data flows in Fabric
  • Hands-on exploration of Gen2 data flow capabilities
  • Using Gen2 flows together with data pipelines
  • Ingesting data using Apache Spark in Fabric
  • Storing structured data in the Lakehouse
  • Analyzing and utilizing loaded datasets
  • Grasping the core principles of Data Factory pipelines
  • Configuring and using copy tasks effectively
  • Applying predefined pipeline templates
  • Triggering, controlling, and monitoring pipelines
  • Structure and concept of the Microsoft Fabric Lakehouse
  • Practical work with the Fabric Lakehouse
  • Using transformation options within the Lakehouse
  • Understanding the layered model of the Medallion architecture
  • Building Bronze, Silver, and Gold layers in the Lakehouse
  • Creating queries and generating reports from the Lakehouse
  • Maintaining and administering Lakehouse environments
  • Setting up and customizing the Spark environment in Fabric
  • Running Spark jobs and evaluating results
  • Performing data transformations with Spark DataFrames
  • Writing and executing queries with Spark SQL
  • Visualizing results in Spark notebooks
  • Core principles and advantages of Delta Lake
  • Creating and managing Delta tables
  • Using Spark for read and write operations on Delta
  • Processing real-time data with Delta Lake
  • Concepts and architecture of modern data warehouses
  • Setting up and using the Fabric Data Warehouse
  • Applying SQL-based queries and transformation logic
  • Preparing data for analytical workloads
  • Access control and monitoring in the Data Warehouse
  • Comparing and selecting different loading strategies
  • Configuring pipelines for warehouse ingestion
  • Writing T-SQL scripts for data imports
  • Using Dataflow Gen2 for transformation and integration
  • Creating queries directly in the integrated SQL editor
  • Getting to know and using the visual query editor
  • Connecting external client tools to the Data Warehouse
  • Analyzing and managing capacity utilization
  • Tracking active processes and workflows in real time
  • Measuring and improving query performance
  • Assessing requirements for scalable data models
  • Implementing proven modeling patterns in Power BI
  • Optimizing configuration and performance for large datasets
  • Reviewing and evaluating existing model relationships
  • Creating and adjusting table relationships deliberately
  • Using DAX expressions for relationship-based calculations
  • Understanding how relationship types affect analysis results
  • Analyzing DAX queries for runtime and efficiency
  • Diagnosing errors in DAX expressions with DAX Studio
  • Identifying model weaknesses with the Best Practice Analyzer
  • Restricting access rights at the model level
  • Securing and controlling sensitive model objects
  • Consistently applying security recommendations in modeling

Frequently asked questions

  • Practical expertise in Microsoft Fabric increases value in modern analytics projects and opens doors to sought-after specialist roles.
  • Those with a foundation in data structures or BI can get started – the course focuses on application rather than frontal instruction.
  • Professionals with Fabric knowledge are in high demand in cloud projects – especially in roles around data architecture, analytics, and business intelligence.
  • Real-world scenarios take center stage: pipelines, lakehouses, and complete analytics workflows are built directly within the platform.
  • Traditional tools increasingly reach their limits in modern data environments – Fabric knowledge closes that gap effectively.
  • Solutions take shape during the training itself and can be put to use immediately in real data and analytics projects.
  • Microsoft Fabric is the central platform – complemented by Data Factory, Synapse components, and Power BI for scalable analytics solutions.
  • The exam sets high standards – the course’s structured approach and direct practical relevance provide a solid foundation for passing it.

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