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Microsoft DP-600 Exam Syllabus

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Before starting your DP-600 exam preparation, it is recommended to review the complete Microsoft Implementing Analytics Solutions Using Microsoft Fabric exam syllabus and carefully go through the exam objectives listed below. Once you understand the exam structure and objectives, you should practice using our free DP-600 questions. We also provide premium DP-600 practice test, fully updated according to the latest exam objectives, to help you accurately assess your preparedness for the actual exam.

Microsoft
Vendor
DP-600
Exam Code
209
Total Questions
3
Total Exam Domains

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DP-600 EXAM QUESTIONS

Microsoft DP-600 Exam Objectives

Section 1: Prepare data
Weight:
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 different data stores
  • Implement OneLake integration for Eventhouse and semantic models
Transform data
  • Create views, functions, and stored procedures
  • Enrich data by adding new columns or 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 by using SQL
  • Select, filter, and aggregate data by using KQL
  • Select, filter, and aggregate data by using DAX
Section 2: Implement and manage semantic models
Weight:
25-30%
Design and build semantic models
  • Choose a storage mode
  • 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 analytics endpoint
  • Implement incremental refresh for semantic models
Section 3: Maintain a data analytics solution
Weight:
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 control
  • 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 deployment pipelines
  • Perform impact analysis of downstream dependencies from lakehouses, warehouses, dataflows, and semantic models
  • Deploy and manage semantic models by using the XMLA endpoint
  • Create and update reusable assets, including Power BI template (.pbit) files, Power BI data source (.pbids) files, and shared semantic models
Info
https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-600