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DP-600T00-A: Microsoft Fabric Analytics Engineer

Microsoft Fabric Analytics Engineer Certification Course

Microsoft Fabric Analytics Engineer Training

This is a four-day instructor-led course that focuses on implementing and managing large-scale data analytics solutions using Microsoft Fabric. Participants with prior analytics experience will explore Microsoft Fabric’s features such as lakehouses, data warehouses, notebooks, dataflows, data pipelines, and semantic models to create and deploy analytics assets.

This course is ideal for individuals with PL-300 certification or equivalent experience in Power BI, along with a background in enterprise-level data analytics solutions.

Microsoft Certified: Fabric Analytics Engineer Associate

The certification exam can be registered and attempted within 3 months of course/module completion at our training centre on weekdays during normal business hours (excludes public holidays)

Microsoft fabric analytics engineer material provided

  • Plan, implement, and manage a solution for data analytics.
  • Prepare and serve data.
  • Implement and manage semantic models.
  • Explore and analyse data

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

  • Introduction to end-to-end analytics using Microsoft Fabric
  • Administer Microsoft Fabric
  • Ingest Data with Dataflows Gen2 in Microsoft Fabric
  • Ingest data with Spark and Microsoft Fabric notebooks
  • Get started with lakehouses in Microsoft Fabric
  • Organize a Fabric lakehouse using medallion architecture design
  • Use Apache Spark in Microsoft Fabric
  • Work with Delta Lake tables in Microsoft Fabric
  • Get started with data warehouses in Microsoft Fabric
  • Load data into a Microsoft Fabric data warehouse
  • Query a data warehouse in Microsoft Fabric
  • Monitor a Microsoft Fabric data warehouse
  • Understand scalability in Power BI
  • Create Power BI model relationships
  • Use tools to optimize Power BI performance
  • Enforce Power BI model security
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