This course covers methods and practices for designing and implementing enterprise-scale analytics solutions using Microsoft Fabric. Learners will build expertise across Fabric workloads including lakehouses, data warehouses, semantic models, notebooks, pipelines, dataflows, and Real-Time Intelligence.The course focuses on preparing, transforming, modeling, governing, and visualizing analytics data using Microsoft Fabric. Students will also learn semantic modeling, DAX optimization, governance with Purview, and AI-ready analytics implementations. 

By the end of this course, learners will be able to design scalable analytics architectures and manage end-to-end analytics solutions using Microsoft Fabric.. 

After completing, DP-600 course student will be able to :

  • Build and manage analytics solutions using Microsoft Fabric
  • Implement lakehouses, warehouses, and Real-Time Intelligence
  • Transform and model analytics data using notebooks, SQL, and dataflows
  • Create and optimize enterprise semantic models using DAX
  • Secure, govern, and maintain analytics assets using Purview and Fabric governance

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Key Features of DP-600:

  • End-to-End Fabric Analytics 

  • Hands-on Labs 

  • Semantic Modeling & DAX 

  • AI-Ready Analytics 

  • Enterprise Governance 

Who should Attend ?

  • Data Engineers
  • Data Analysts
  • BI Developers
  • Fabric Administrators
  • Power BI Professionals

Prerequisites of DP-600

  • Basic knowledge of data engineering concepts
  • Familiarity with SQL and Python/Scala
  • Foundational understanding of analytics concepts
  • Familiarity with Power BI
  • Understanding of cloud computing (Azure preferred)
  • Basic knowledge of big data concepts and ETL processes
  • Exposure to Spark (recommended but not mandatory)

Why choose CloudThat as your training partner?

  • CloudThat provides Microsoft-certified trainers with deep expertise in Microsoft Fabric, Spark and real-world data engineering implementations. 
  • Hands-on labs and industry-focused scenarios ensure practical exposure to building scalable data pipelines and optimizing big data workloads. 
  • Comprehensive coverage of certification topics with exam-focused preparation materials and mock assessments aligned to DP-600 objectives. 
  • Flexible delivery options including corporate training, instructor-led online sessions and customized enterprise learning paths. 
  • Post-training support, recorded sessions and continuous learning resources help reinforce knowledge and support certification success. 
  • Proven track record in delivering high-quality Azure and data engineering training to professionals across multiple industries. 

Learning objectives of DP-600

  • Prepare and transform analytics data 
  • Implement semantic models using Power BI and DAX 
  • Design lakehouse and warehouse architectures 
  • Govern analytics assets in Microsoft Fabric 
  • Implement AI-ready semantic layers 
  • Manage analytics development lifecycle 

Course Outline of DP-600 Download Course Outline

Explore Analytics Data Stores in Microsoft Fabric

  • Introduction to end-to-end analytics in Microsoft Fabric
  • Discover and connect to data in OneLake
  • Get started with lakehouses in Microsoft Fabric
  • Get started with data warehouses in Microsoft Fabric
  • Get started with Real-Time Intelligence
  • Lab: Discover and connect to data in OneLake
  • Lab: Create a Microsoft Fabric lakehouse
  • Lab: Create and query a data warehouse
  • Lab: Get started with Real-Time Intelligence

Design and Transform Analytics Data in Microsoft Fabric

  • Choose data stores in Microsoft Fabric
  • Design dimensional models for analytics
  • Transform data using Dataflows Gen2
  • Transform data using notebooks in Microsoft Fabric
  • Transform data using T-SQL in Fabric warehouses
  • Lab: Design and implement a dimensional model
  • Lab: Transform data using dataflows
  • Lab: Transform data using notebooks
  • Lab: Transform data using T-SQL

  • Create DAX calculations in semantic models
  • Design semantic models for scalability
  • Optimize semantic model performance
  • Enforce semantic model security
  • Manage semantic model lifecycle
  • Lab: Create DAX calculations
  • Lab: Build scalable semantic models
  • Lab: Diagnose and optimize slow reports
  • Lab: Implement Row-Level Security (RLS)
  • Lab: Manage semantic model lifecycle

Prepare AI-Ready Analytics Data in Microsoft Fabric

  • Prepare semantic layer for AI
  • Understand Microsoft Fabric IQ fundamentals
  • Create ontology with Fabric IQ
  • Lab: Prepare semantic model for AI
  • Lab: Build ontology manually
  • Lab: Generate ontology from semantic model

Secure and Govern Analytics Data in Microsoft Fabric

  • Secure data access in Microsoft Fabric
  • Secure Fabric data warehouses
  • Govern analytics data with Microsoft Purview
  • Implement governance policies in Fabric
  • Lab: Secure analytics access
  • Lab: Secure data warehouses
  • Lab: Govern analytics assets in Fabric

Certification details of DP-600

    • DP-600 certification validates skills in implementing enterprise-scale analytics solutions using Microsoft Fabric and Power BI technologies.
    • The exam evaluates abilities in data preparation, lakehouse and warehouse implementation, semantic modeling, data transformation, and analytics solution optimization within Microsoft Fabric.
    • Candidates are expected to demonstrate knowledge of OneLake, Dataflows Gen2, notebooks, DAX calculations, Real-Time Intelligence, governance, and semantic model performance tuning.
    • Certification aligns with the Fabric Analytics Engineer role, focusing on modern analytics architectures, AI-ready analytics solutions, data governance, and enterprise reporting capabilities.

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Course ID: 29124

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FAQs of DP-600: Fabric Analytics Engineer – Implement Analytics Solutions Using Microsoft Fabric

DP-600 validates skills for implementing enterprise analytics solutions using Microsoft Fabric.

Yes. The course includes labs on lakehouses, semantic models, notebooks, and governance.

Microsoft Fabric, Power BI, OneLake, Dataflows Gen2, DAX, KQL, SQL, and Purview.

Data engineers, analysts, BI developers, and Fabric professionals.

Basic Power BI understanding is recommended but not mandatory.

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