Exam Prep Hub for DP-600: Implementing Analytics Solutions Using Microsoft Fabric

This is your one-stop hub with information for preparing for the DP-600: Implementing Analytics Solutions Using Microsoft Fabric certification exam. Upon successful completion of the exam, you earn the Fabric Analytics Engineer Associate certification.

This hub provides information directly here, links to a number of external resources, tips for preparing for the exam, practice tests, and section questions to help you prepare. Bookmark this page and use it as a guide to ensure that you are fully covering all relevant topics for the exam and using as many of the resources available as possible. We hope you find it convenient and helpful.

Why do the DP-600: Implementing Analytics Solutions Using Microsoft Fabric exam to gain the Fabric Analytics Engineer Associate certification?

Most likely, you already know why you want to earn this certification, but in case you are seeking information on its benefits, here are a few:
(1) there is a possibility for career advancement because Microsoft Fabric is a leading data platform used by companies of all sizes, all over the world, and is likely to become even more popular
(2) greater job opportunities due to the edge provided by the certification
(3) higher earnings potential,
(4) you will expand your knowledge about the Fabric platform by going beyond what you would normally do on the job and
(5) it will provide immediate credibility about your knowledge, and
(6) it may, and it should, provide you with greater confidence about your knowledge and skills.


Links to important DP-600 resources:


DP-600: Skills measured as of October 31, 2025:

Here you can learn in a structured manner by going through the topics of the exam one-by-one to ensure full coverage; click on each hyperlinked topic to go to more information about it:

Maintain a data analytics solution (25%-30%)

Implement security and governance

Implement workspace-level access controls

Implement item-level access controls

Implement row-level, column-level, object-level, and file-level access controls

Apply sensitivity labels to items

Endorse items

Maintain the analytics development lifecycle

Configure version control for a workspace

Create and manage a Power BI Desktop project (.pbip)

Create and configure development pipelines

Perform impact analysis of downstream dependencies from lakehouses, data warehouses, dataflows, and semantic models

Deploy and manage semantic models using XMLA endpoint

Create and update reusable assets, including Power BI template (.pbit) files, Power BI data source (.pbids) files, and shared semantic models

Prepare data (45%-50%)

Get Data

Create a data connection

Discover data by using OneLake catalog and Real-Time Hub

Ingest or access data as needed

Choose between a lakehouse, warehouse, or eventhouse

Implement OneLake Integration for eventhouse and semantic models

Transform Data

Create views, functions, and stored procedures

Enrich data by adding new columns and tables

Implement a star schema for a lakehouse or warehouse

Denormalize data

Aggregate data

Merge or join data

Identify and resolve duplicate data, missing data, or null values

Convert column data types

Filter data

Query and analyze data

Select, filter, and aggregate data by using the Visual Query Editor

Select, filter, and aggregate data using SQL

Select, filter, and aggregate data by using KQL

Select, filter, and aggregate data by using DAX

Implement and manage semantic models (25%-30%)

Design and build semantic models

Choose a storage mode

Choose a storage mode – additional information

Implement a star schema for a semantic model

Implement relationships, such as bridge tables and many-to-many relationships

Write calculations that use DAX variables and functions, such as iterators, table filtering, windowing, and information functions

Implement calculation groups, dynamic format strings, and field parameters

Identify use cases for and configure large semantic model storage format

Design and build composite models

Optimize enterprise-scale semantic models

Implement performance improvements in queries and report visuals

Improve DAX performance

Configure Direct Lake, including default fallback and refresh behavior

Choose between Direct Lake on OneLake and Direct Lake on SQL endpoints

Implement incremental refresh for semantic models


Practice Exams:

We have provided 2 practice exams with answers to help you prepare.

DP-600 Practice Exam 1 (60 questions with answer key)

DP-600 Practice Exam 2 (60 questions with answer key)


Good luck to you passing the DP-600: Implementing Analytics Solutions Using Microsoft Fabric certification exam and earning the Fabric Analytics Engineer Associate certification!

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