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Microsoft DP-600 Fabric Analytics Practice Test

Try 12 Microsoft Fabric Analytics Engineer Associate (DP-600) sample questions and practice-test preview prompts on semantic models, lakehouses, warehouses, Power BI, optimization, governance, and analytics engineering scope.

DP-600 is Microsoft Certified: Fabric Analytics Engineer Associate for candidates who design, create, deploy, secure, and maintain enterprise-scale analytics assets in Microsoft Fabric, including semantic models, warehouses, lakehouses, SQL, KQL, DAX, and business-facing analytics delivery.

IT Mastery coverage for DP-600 is under review. Use this page to try 12 original sample questions, review the exam snapshot, route fit, and related live data-platform practice options.

Practice option: Sample questions available

DP-600: Microsoft Fabric Analytics Engineer Associate practice update

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Who DP-600 is for

  • Fabric analytics engineers building enterprise-scale analytics solutions
  • candidates who work with semantic models, warehouses, lakehouses, DAX, SQL, KQL, Power BI-style analytics, and governance
  • teams comparing Fabric analytics engineering with data engineering, Databricks, Snowflake, or broader analytics-platform work

DP-600 exam snapshot

  • Issuer: Microsoft
  • Official certification name: Microsoft Certified: Fabric Analytics Engineer Associate
  • Exam code: DP-600
  • Product: Microsoft Fabric
  • Exam time shown by Microsoft Learn: 100 minutes
  • Renewal frequency shown by Microsoft Learn: 12 months
  • Current IT Mastery status: Sample questions

Topic coverage for DP-600

Area assessed by MicrosoftPractical focus
Maintain a data analytics solutionSecure, maintain, govern, and operate analytics assets.
Prepare dataPrepare and enrich data using Fabric analytics workflows.
Implement and manage semantic modelsBuild model logic, relationships, measures, and analytical delivery structures.

Use these live IT Mastery pages now

If you need to practice…Best pageWhy
Databricks analytics and lakehouse contextDatabricks Data Engineer AssociateUseful live route for lakehouse concepts and data workflow judgment.
Snowflake analytics platform workSnowPro CoreGood live route for warehouse architecture, security, and analytics platform fundamentals.
Azure fundamentalsAZ-900Useful Microsoft cloud foundation before Fabric-specific coverage is live.

Practice options

  • Current status: Sample questions
  • IT Mastery coverage for this exam: under review
  • Best use right now: try the 12 sample questions, confirm DP-600 as your target, then practise related cloud data and Microsoft fundamentals routes while coverage expands
  • Update form: use the Notify me form near the top of this page if DP-600 is your actual target exam
  • Quick review: open the DP-600 cheat sheet before the sample questions if you need a compact Fabric analytics checklist.

Sample Exam Questions

Try these 12 original sample questions for Microsoft DP-600. They are designed for self-assessment and are not official exam questions.

Question 1

Topic: Fabric architecture

A team needs lakehouse storage, semantic models, and Power BI-style delivery in one analytics platform. What should be evaluated?

  • A. Microsoft Fabric workspace architecture, lakehouse or warehouse choice, semantic model, and governance.
  • B. A desktop-only spreadsheet.
  • C. A DNS forwarding rule.
  • D. A Teams ringtone policy.

Best answer: A

Explanation: DP-600 centers on enterprise analytics assets in Microsoft Fabric.

What this tests: Designing Fabric analytics solutions.


Question 2

Topic: semantic model

Reports show inconsistent revenue totals across pages. What should be reviewed?

  • A. Only visual colors.
  • B. Semantic model measures, relationships, filter context, and metric definitions.
  • C. The report title font.
  • D. A mailbox rule.

Best answer: B

Explanation: Fabric analytics engineers need strong semantic modeling and metric governance.

What this tests: Managing semantic models.


Question 3

Topic: DAX

A measure should calculate sales for the same period last year. What skill is most relevant?

  • A. A DNS TXT record.
  • B. A VM patch schedule.
  • C. DAX time-intelligence logic that respects model relationships and filter context.
  • D. A Teams meeting policy.

Best answer: C

Explanation: DP-600 includes model logic and analytics behavior, including DAX where relevant.

What this tests: Applying DAX in Fabric analytics.


Question 4

Topic: data preparation

Raw data has duplicate customer records before analytics modeling. What should be done?

  • A. Ignore duplicates.
  • B. Hide bad rows in visuals only.
  • C. Publish without validation.
  • D. Clean, deduplicate, and validate data in the preparation layer before publishing analytics assets.

Best answer: D

Explanation: Data preparation quality affects downstream models and reports.

What this tests: Preparing data for analytics.


Question 5

Topic: workspace governance

Different teams need separate development and production analytics workspaces. What should be planned?

  • A. Workspace roles, deployment process, endorsement, security, and lifecycle governance.
  • B. Everyone as workspace admin.
  • C. No deployment process.
  • D. One personal workspace for production.

Best answer: A

Explanation: Fabric solutions require governance around workspaces, roles, and release flow.

What this tests: Governing Fabric workspaces.


Question 6

Topic: lakehouse vs warehouse

A team needs SQL analytics over curated relational-style tables. What should be compared?

  • A. Only a PowerPoint file.
  • B. Fabric warehouse and lakehouse patterns based on data shape, SQL needs, and workload design.
  • C. A DNS zone.
  • D. A local text document.

Best answer: B

Explanation: Fabric includes multiple analytical storage and processing options. Choice should match workload needs.

What this tests: Choosing Fabric data architecture.


Question 7

Topic: security

Executives should see all regions, but regional managers should see only their own region. What should be implemented?

  • A. Public access to all reports.
  • B. No permission testing.
  • C. Role and data-security design such as row-level security where appropriate.
  • D. One shared account.

Best answer: C

Explanation: Analytics assets need data access controls aligned to user roles.

What this tests: Securing analytics data.


Question 8

Topic: performance

A report is slow after a model grows. What should be reviewed?

  • A. Only report wallpaper.
  • B. No diagnostics.
  • C. More visuals on the same page.
  • D. Model design, measure efficiency, relationships, aggregations, refresh, and capacity behavior.

Best answer: D

Explanation: DP-600 candidates should optimize semantic models and analytics assets.

What this tests: Troubleshooting analytics performance.


Question 9

Topic: KQL and SQL

An analytics solution uses both event data and relational data. What should the engineer understand?

  • A. When to use KQL, SQL, lakehouse, warehouse, and semantic modeling capabilities.
  • B. Use one language for every workload.
  • C. Avoid querying entirely.
  • D. Export everything manually.

Best answer: A

Explanation: Fabric analytics can span multiple query and modeling approaches.

What this tests: Choosing query and analytics tools.


Question 10

Topic: refresh and pipelines

A semantic model refresh fails after upstream schema changes. What should be checked?

  • A. Only the visual theme.
  • B. Pipeline status, schema drift, credentials, dependencies, and refresh logs.
  • C. A user’s keyboard.
  • D. A Teams avatar.

Best answer: B

Explanation: Refresh issues often come from upstream dependency changes and credentials.

What this tests: Troubleshooting refresh dependencies.


Question 11

Topic: certification fit

A learner mainly builds Fabric reports and semantic models, not low-level Spark pipelines. Which Fabric route is closer?

  • A. DP-700 data engineer only.
  • B. AZ-140 only.
  • C. DP-600 analytics engineer.
  • D. MS-721 only.

Best answer: C

Explanation: DP-600 is the Fabric Analytics Engineer route; DP-700 is more data-engineering oriented.

What this tests: Distinguishing Fabric analytics and data engineering.


Question 12

Topic: business delivery

A model is technically correct but business users do not trust the numbers. What should be improved?

  • A. Tell users to trust it.
  • B. Hide data sources.
  • C. Avoid documenting calculations.
  • D. Metric definitions, lineage, validation, stakeholder review, and documentation.

Best answer: D

Explanation: Analytics engineering includes trust, definitions, and validation, not only technical build.

What this tests: Improving trust in analytics assets.


DP-600 Fabric analytics map

Use this map to connect the sample questions to Fabric analytics engineering decisions.

    flowchart LR
	  S1["Analytics requirement"] --> S2
	  S2["Prepare and transform data"] --> S3
	  S3["Build semantic model"] --> S4
	  S4["Secure and govern assets"] --> S5
	  S5["Publish reports and metrics"] --> S6
	  S6["Maintain refresh and performance"]

Quick Cheat Sheet

CueWhat to remember
Semantic modelDesign measures, relationships, and calculation logic around business questions.
Fabric assetsUnderstand lakehouse, warehouse, semantic model, notebook, pipeline, and report responsibilities.
GovernancePlan workspaces, permissions, endorsement, lineage, and data protection.
PerformanceReview model design, DAX, refresh, aggregation, and query patterns.
OperationsMonitor refresh, usage, failures, and change impact after publishing.

Mini Glossary

  • DAX: Formula language used for analytics measures and model calculations.
  • Lakehouse: Fabric data architecture combining lake storage with table and analytics features.
  • Semantic model: Business-facing model used by reports and analytical tools.
  • Warehouse: SQL analytics storage pattern for structured enterprise reporting.
  • Workspace: Fabric container for organizing and securing analytics assets.

Microsoft DP-600 practice update

Use this page to review DP-600 sample questions and use the Notify me form for updates. The related pages below help you compare adjacent IT Mastery Microsoft Fabric practice options before choosing what to study next.

Official sources

What to open next

In this section

  • Microsoft DP-600 Cheat Sheet: Fabric Analytics
    Review Microsoft Fabric Analytics Engineer Associate (DP-600) semantic models, lakehouses, warehouses, DAX, governance, optimization, and analytics-engineering traps before using the DP-600 practice page.
Revised on Monday, May 25, 2026