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DP-600: Microsoft Fabric Analytics Engineer Training

DP-600: Microsoft Fabric Analytics Engineer Training
DP-600: Microsoft Fabric Analytics Engineer Training course covers methods and practices for implementing and managing enterprise-scale data analytics solutions using Microsoft Fabric. Students will learn how to use Fabric dataflows, pipelines, and notebooks to develop analytics assets such as semantic models, data warehouses, and lakehouses.


This course is designed for experienced data professionals skilled at data preparation, modeling, analysis, and visualization, such as the PL-300: Power BI Data Analyst certification. Learners should have prior experience with one of the following programming languages: Structured Query Language (SQL), Kusto Query Language (KQL), or Data Analysis Expressions (DAX).


This course includes exercises to enable you to learn practical skills with the technologies. By the end of the course, students will learn how to implement end-to-end analytics solutions with Microsoft Fabric. You'll learn how to


  • Prepare and enrich data for analysis
  • Secure and maintain analytics assets
  • Implement and manage semantic models

Advance Your Skills with Flexmind (Microsoft Partner)

Who should attend the DP-600 Training?

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For Professionals

The course is ideal for professionals seeking in-depth knowledge of data engineering using Microsoft Fabric and optionally preparing for the DP‑600 certification exam, leading to the Microsoft Certified: Fabric Analytics Engineer Associate credential.

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For Businesses

DP-600 training enables faster analytics delivery, optimized Fabric costs, reduced consultant dependency, improved data quality, and stronger ROI-driven business decisions.

Prerequisites for the DP-600: Microsoft Fabric Analytics Engineer Course

While there are no required prerequisites for taking this course, it is recommended that students have:


  • A foundational knowledge of core data concepts and how they’re implemented using Microsoft data services. For more information see Azure Data Fundamentals.
  • Experience designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value using Microsoft Power BI. For more information see Power BI Data Analyst.

Key Features of Flexmind DP-600 Training

Flexmind provides this training in both online and offline modes in a comprehensive manner. It is designed in line with the latest exam requirements. The key features of this training are as follows:

4 Day · 32 Hours
Microsoft Certified Trainer
Official Courseware
Official Lab Access
Applied Workshop

Course Duration

The course has a total duration of 32 hours and is completed over 4 days.

Instructor-Led Training

This training is delivered by a senior Microsoft Certified Trainer with deep, hands‑on experience in enterprise‑scale Microsoft Fabric implementations.

Microsoft Official Courseware

The program is delivered by Flexmind using Microsoft Courseware. You’ll work through study material, labs and applied workshops. The instructor guides you throughout the learning journey.

Applied Workshop

The applied workshop will take place on the final day of the course. It will help you practice the skills that you’ve learned. Here, learners are provided with options for scenarios from which they can pick the one they want to build. They will be required to create their own solution to the stated problem and any required automation.

Course Completion Certificate


A certification is awarded at the end of the course. This validates skills gained and adds credibility to your resume.

Course Outline

Module 1: Explore end-to-end analytics with Microsoft Fabric

  • Describe end-to-end analytics in Microsoft Fabric
  • Understand data teams and roles that use Fabric
  • Describe how to enable and use Fabric

Module 2: Get started with lakehouses in Microsoft Fabric

  • What is a lakehouse?
  • Load data into a lakehouse
  • Explore, transform, and visualize data in the lakehouse
  • Lab - Create a Microsoft Fabric Lakehouse

Module 3: Ingest data with Dataflow Gen2 in Microsoft Fabric

  • Understand Dataflow Gen2
  • Explore Dataflow Gen2
  • Integrate Dataflow Gen2 and pipelines

Module 4: Orchestrate processes and data movement with Microsoft Fabric

  • Pipelines in Microsoft Fabric
  • Run and monitor pipelines
  • Lab - Ingest data with a pipeline in Microsoft Fabric

Module 5: Use Apache Spark in Microsoft Fabric

  • What is Apache Spark?
  • Run Spark in Fabric
  • Load data in a Spark Dataframe
  • Work with data using Spark SQL
  • Visualize data
  • Lab - Analyze data with Apache Spark

Module 6: Get started with data warehouses in Microsoft Fabric

  • Data warehouse fundamentals
  • Design a data warehouse
  • Special types of dimension tables
  • Ingest data into a data warehouse
  • Query data
  • Build relationships
  • Security overview
  • Lab - Analyze data in a data warehouse

Module 7: Load data into a Microsoft Fabric data warehouse

  • Understand ETL (Extract, Transform and Load)
  • Stage the data
  • Different data load types
  • Dimension keys
  • Load dimension tables and fact tables
  • Load data with Fabric pipelines
  • Transform data with Copilot
  • Lab - Load data into a data warehouse in Microsoft Fabric
  • Lab - Query a data warehouse in Microsoft Fabric

Module 8: Query a data warehouse in Microsoft Fabric

  • Aggregate measures by dimension attributes
  • Joins in a snowflake schema
  • Use ranking functions
  • DAX calculations
  • Aggregate measures

Module 9: Monitor a Microsoft Fabric data warehouse

  • Monitor capacity metrics
  • Usage considerations
  • Monitor current activity
  • Query insights views
  • Lab - Monitor a data warehouse in Microsoft Fabric

Module 10: Secure a Microsoft Fabric data warehouse

  • Dynamic Data Masking
  • Masking Rules
  • Row-level security
  • Column-level security
  • Granular permissions using T-SQL
  • Lab - Secure a warehouse in Microsoft Fabric

Module 11: Add measures to Power BI semantic models

  • What is DAX?
  • Create measures
  • CALCULATE() function
  • Semi-additive measures
  • Time Intelligence functions
  • Create calculated tables
  • Lab - Create DAX calculations in Power BI Desktop

Module 12: Design scalable semantic models

  • Enterprise-scale data: defined
  • How do I design for scalability?
  • Choose storage mode and design a model
  • Work with relationships
  • Write DAX for readability with complex calculations
  • Create dynamic calculation elements
  • Lab - Design a scalable semantic model

Module 13: Optimize a model for performance in Power BI

  • Optimize Power BI solutions
  • Tune report performance

Module 14: Create and manage Power BI assets

  • Create reusable Power BI assets
  • Develop with Power BI Projects
  • Use Deployment pipelines
  • Lab - Create reusable Power BI assets

Module 15: Enforce semantic model security

  • Security overview in Power BI
  • Configure roles with Static method
  • Use a dynamic value with DAX filters
  • Restrict Access to Power BI model objects
  • Lab - Enforce model security

Module 16: Get started with Real-Time Intelligence with Microsoft Fabric

  • What is Real-Time Intelligence?
  • What is the Kusto Query Language (KQL)
  • Write KQL queries
  • Using render expressions in KQL
  • Lab - Get started with Real-Time Intelligence in Microsoft Fabric

Module 17: Secure data access in Microsoft Fabric

  • Understand the Fabric security model
  • Data security design
  • Understand workspace roles
  • Configure workspace and item-level permissions
  • Use T-SQL to configure granular permissions
  • Lab - Secure data access in Microsoft Fabric

Module 18: Administer Microsoft Fabric

  • Understand the Fabric Architecture
  • Fabric admin portal
  • Manage Fabric security
  • Assign and manage user licenses
  • Govern data in Fabric

Class Schedule

Instructor-Led Training

  • 32 Hours of Instructor-Led Training
  • One-to-one doubt resolution sessions
  • Microsoft Official Lab Access

Learning Objectives

The DP-600: Microsoft Fabric Analytics Engineer training course is designed for experienced data professionals skilled at data preparation, modeling, analysis, and visualization. The DP-600: Microsoft Fabric Analytics Engineer training course covers topics including:


  • Preparing and enriching data for analysis
  • Securing and maintaining analytics assets
  • Implementing and managing semantic models

About DP-600 Exam


To help you understand the assessment better, here are a few important details about the exam.


Exam Name DP-600: Microsoft Fabric Analytics Engineer
Who can Apply Appropriate for Data Engineer, Data Analyst
Duration of Exam 100 Minutes
Fees Rs. 4,865 (India), $165 USD (United States)
Level of Difficulty Intermediate
Type of Credential Microsoft Certification
Languages English, Japanese, Chinese (Simplified), German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia)
Exam Retake Exam retake allowed after 24 hours
Quality Check during Assessment The online exam is proctored

The table below represents the weightage of each study area in the exam. Areas with higher percentages are expected to have more questions.

Study Area Percentage
Maintain a data analytics solution 25-30%
Prepare data 45-50%
Implement and manage semantic models 25-30%

How do our DP-600: Microsoft Fabric Analytics Engineer Training Course Work?

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Sharpen your skills by learning through course assignments, live projects, and regular assessments and quizzes.

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Resolve your queries from industry experts with our dedicated one-to-one doubt-clearing sessions.

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Reviews

FAQ's About DP-600: Microsoft Fabric Analytics Engineer Training Course

The DP‑600 course is designed to help learners build expertise in designing, implementing, and managing enterprise‑scale analytics solutions using Microsoft Fabric. The course focuses on preparing, modeling, securing, and serving data using Fabric components such as lakehouses, data warehouses, semantic models, pipelines, and reports.

This course is ideal for data professionals such as Data Analysts, Analytics Engineers, Data Engineers, BI Professionals, and Power BI Developers who want to work with Microsoft Fabric to create and deploy end‑to‑end analytics solutions and earn the Microsoft Certified: Fabric Analytics Engineer Associate credential.

Learners should have a foundational understanding of data analytics concepts, experience with data modeling and transformation, and familiarity with Power BI. Knowledge of SQL, DAX, or KQL is recommended to effectively work with Microsoft Fabric analytics assets.

By completing this course, learners will gain skills in preparing and enriching data for analysis, implementing and managing semantic models, securing and maintaining analytics assets, and analyzing data using Microsoft Fabric tools and services.

The DP‑600 Microsoft Fabric Analytics Engineer Training is delivered over 4 days of instructor‑led training, providing in‑depth coverage of Microsoft Fabric analytics concepts aligned with the DP‑600 exam objectives.

Yes, this course is aligned with the official DP‑600 study guide and Microsoft Learn curriculum and is designed to prepare learners to successfully pass the DP‑600: Implementing Analytics Solutions Using Microsoft Fabric certification exam.

The DP‑600 course is delivered by a Microsoft Certified Trainer (MCT) with hands‑on experience in Microsoft Fabric and enterprise analytics implementations, ensuring a balance of certification readiness and practical understanding.

The course includes guided demonstrations and scenario‑based discussions that reflect real‑world analytics challenges, helping learners understand how to design and manage analytics solutions using Microsoft Fabric in enterprise environments.

After successfully passing the DP‑600 exam, candidates earn the Microsoft Certified: Fabric Analytics Engineer Associate certification, validating their expertise in building and managing analytics solutions using Microsoft Fabric.

Yes, the DP‑600 course is suitable for corporate and enterprise teams seeking to upskill data professionals responsible for analytics, reporting, and data modeling using Microsoft Fabric in modern data platforms.

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