Microsoft DP-600 Exam Details & Actual Exam Questions

Exam Code/Number: DP-600
Exam Name/Title: Implementing Analytics Solutions Using Microsoft Fabric
Certification Provider: Microsoft
Corresponding Certification: Microsoft Certified

Exam Questions: 203
Updated On: Aug,21 2026
Certification Level: Associate

Microsoft Implementing Analytics Solutions Using Microsoft Fabric Exam Questions

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Microsoft DP-600 Exam Overview:

Certification Vendor:	Microsoft
Exam Name:	Implementing Analytics Solutions Using Microsoft Fabric
Exam Number:	DP-600
Certificate Validity Period:	2 years
Passing Score:	700 / 1000
Exam Format:	Multiple choice, Case study, Scenario-based
Available Languages:	English, Japanese, Chinese (Simplified), German, French, Spanish, Portuguese (Brazil)
Exam Duration:	100 minutes
Exam Price:	USD 165
Real Exam Qty:	40–60
Recommended Training:	Microsoft Learn: DP-600 Learning Path
Exam Registration:	Microsoft Certification Exam Registration
Sample Questions:	Microsoft DP-600 Sample Questions
Exam Way:	Online proctored or onsite at authorized test centers
Pre Condition:	No mandatory prerequisites; recommended experience with data modeling, SQL, DAX, and Microsoft Fabric components
Official Syllabus URL:	https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-600

Microsoft DP-600 Exam Syllabus Topics:

Section

Weight

Objectives

Maintain a data analytics solution

25–30

- Implement security and governance

1. Use sensitivity labels and endorsement
2. Configure workspace and item-level access
3. Apply row-level, column-level, and object-level security

- Manage analytics development lifecycle

1. Configure version control and projects
2. Perform impact analysis and dependency management
3. Implement deployment pipelines

Implement and manage semantic models

25–30

- Design and build semantic models

1. Create Power BI semantic models
2. Define relationships, hierarchies, and measures
3. Optimize model performance and structure

- Deploy and maintain semantic models

1. Use XMLA endpoint for deployment and management
2. Create reusable assets and shared models
3. Monitor and refresh semantic models

Prepare data for analytics

45–50

- Implement data storage structures

1. Implement delta lake and partitioning
2. Configure warehouse storage and querying
3. Design and manage lakehouse tables

- Ingest and load data

1. Use Dataflows Gen2 to transform data
2. Ingest data from various sources
3. Load data into lakehouses and warehouses

- Clean and transform data

1. Perform data enrichment and validation
2. Manage data quality and consistency
3. Process data using Spark notebooks and SQL