DP-600: Microsoft Fabric Analytics Engineer

Length: 4 Day(s)     Cost:$3200 + GST

= Scheduled class     = Guaranteed to run     = Fully booked

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LOCATION February March April May
Auckland
Hamilton
Christchurch
Wellington
Virtual Class

This course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will build on existing analytics experience and will learn how to use Microsoft Fabric components, including lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models, to create and deploy analytics assets.

This course is best suited for those who have the PL-300 certification or similar expertise in using Power BI for data transformation, modeling, visualization, and sharing. Also, learners should have prior experience in building and deploying data analytics solutions at the enterprise level.


The primary audience for this course is data professionals with experience in data modeling, extraction, and analytics. DP-600 is designed for professionals who want to use Microsoft Fabric to create and deploy enterprise-scale data analytics solutions.


- Basic understanding of Microsoft Azure services
- Familiarity with data engineering concepts
- Knowledge of SQL language
- Experience in working with both relational and non-relational databases
- Understanding of programming languages such as Python or C#
- Prior experience in using data analytics tools and methods.


The DP-600 course enhances knowledge on designing and implementing data models and data analytics solutions. It provides expertise in managing and developing data processing, monitoring and optimizing data solutions, and designing Azure data storage solutions. This can significantly improve statistical data analysis and interpretation skills, providing a valuable edge in data-driven sectors.


Module 1 - Ingest Data with Dataflows Gen2 in Microsoft Fabric

  • Describe Dataflow (Gen2) capabilities in Microsoft Fabric
  • Create Dataflow (Gen2) solutions to ingest and transform data
  • Include a Dataflow (Gen2) in a pipeline

Module 2 - Ingest data with Spark and Microsoft Fabric Notebooks

  • Ingest external data to Fabric lakehouses using Spark
  • Configure external source authentication and optimization
  • Load data into lakehouse as files or as Delta tables

Module 3 - Use Data Factory pipelines in Microsoft Fabric

  • Describe pipeline capabilities in Microsoft Fabric
  • Use the Copy Data activity in a pipeline
  • Create pipelines based on predefined templates
  • Run and monitor pipelines

Module 4 - Get started with lakehouses in Microsoft Fabric

  • Describe core features and capabilities of lakehouses in Microsoft Fabric
  • Create a lakehouse
  • Ingest data into files and tables in a lakehouse
  • Query lakehouse tables with SQL

Module 5 - Organize a Fabric lakehouse using medallion architecture design

  • Describe the principles of using the medallion architecture in data management.
  • Apply the medallion architecture framework within the Microsoft Fabric environment.
  • Analyze data stored in the lakehouse using DirectLake in Power BI.
  • Describe best practices for ensuring the security and governance of data stored in the medallion architecture.