This post is a part of the DP-600: Implementing Analytics Solutions Using Microsoft Fabric Exam Prep Hub. Bookmark this hub and use it as a guide to help you prepare for the DP-600 certification exam.

This is a practice exam for the
DP-600: Implementing Analytics Solutions Using Microsoft Fabric
certification exam.
– It contains: 60 Questions (the questions are of varying type and difficulty)
– The answer key is located: at the end of the exam; i.e., after all the questions. We recommend that you try to answer the questions before looking at the answers.
– Upon successful completion of the official certification exam, you earn the Fabric Analytics Engineer Associate certification.

Good luck to you!

Section A – Prepare Data (1–24)

Question 1 (Single Choice)

You need to ingest semi-structured JSON files from Azure Blob Storage into a Fabric Lakehouse and apply light transformations using a graphical interface. What is the best tool?

A. Spark notebook
B. SQL endpoint
C. Dataflow Gen2
D. Eventstream

Question 2 (Multi-Select)

Which operations are best performed in Power Query during data preparation? (Choose 2)

A. Removing duplicates
B. Creating DAX measures
C. Changing column data types
D. Creating calculation groups
E. Managing relationships

Question 3 (Single Choice)

Which Fabric feature allows you to reference data stored in another workspace without copying it?

A. Pipeline
B. Dataflow Gen2
C. Shortcut
D. Deployment rule

Question 4 (Single Choice)

Which statement about OneLake is correct?

A. It only supports structured data
B. It replaces Azure Data Lake Gen2
C. It provides a single logical data lake across Fabric
D. It only supports Power BI datasets

Question 5 (Matching)

Match the Fabric item to its primary use case:

Item	Use Case
1. Warehouse	A. Streaming analytics
2. Lakehouse	B. Open data + Spark
3. Eventhouse	C. Relational SQL analytics

Question 6 (Single Choice)

You are analyzing IoT telemetry data with time-based aggregation requirements. Which query language is most appropriate?

A. SQL
B. DAX
C. KQL
D. MDX

Question 7 (Single Choice)

Which transformation is most likely to prevent query folding?

A. Filtering rows
B. Removing columns
C. Merging queries using a fuzzy match
D. Sorting data

Question 8 (Multi-Select)

What are benefits of using Dataflow Gen2? (Choose 2)

A. Reusable transformations
B. High-concurrency reporting
C. Centralized data preparation
D. DAX calculation optimization
E. XMLA endpoint access

Question 9 (Single Choice)

Which file format is optimized for Direct Lake access?

A. CSV
B. JSON
C. Parquet
D. Excel

Question 10 (Fill in the Blank)

Incremental refresh requires two parameters named __________ and __________.

Question 11 (Single Choice)

You want to aggregate data at ingestion time to reduce dataset size. Where should this occur?

A. Power BI visuals
B. DAX measures
C. Power Query
D. Report filters

Question 12 (Multi-Select)

Which characteristics describe a star schema? (Choose 2)

A. Central fact table
B. Snowflaked dimensions
C. Denormalized dimensions
D. Many-to-many relationships by default
E. High cardinality dimensions

Question 13 (Single Choice)

Which action most negatively impacts VertiPaq compression?

A. Using integers instead of strings
B. Reducing cardinality
C. Using calculated columns
D. Sorting dimension tables

Question 14 (Single Choice)

Which Fabric feature provides end-to-end data lineage visibility?

A. Deployment pipelines
B. Impact analysis
C. Lineage view
D. Git integration

Question 15 (Single Choice)

What is the primary purpose of Detect data changes in incremental refresh?

A. Reduce model size
B. Trigger refresh only when data changes
C. Enforce referential integrity
D. Improve DAX performance

Question 16 (Single Choice)

Which Fabric item supports both Spark and SQL querying of the same data?

A. Warehouse
B. Eventhouse
C. Lakehouse
D. Semantic model

Question 17 (Multi-Select)

Which scenarios justify using Spark notebooks? (Choose 2)

A. Complex transformations
B. Streaming ingestion
C. Simple joins
D. Machine learning workflows
E. Report filtering

Question 18 (Single Choice)

Which query type is most efficient for large-scale aggregations on relational data?

A. DAX
B. SQL
C. M
D. Python

Question 19 (Single Choice)

Which Fabric feature enables schema-on-read?

A. Warehouse
B. Lakehouse
C. Semantic model
D. SQL endpoint

Question 20 (Single Choice)

Which approach preserves historical dimension values?

A. Type 1 SCD
B. Type 2 SCD
C. Snapshot fact table
D. Slowly changing fact

Question 21 (Single Choice)

Which tool helps identify downstream impact before changing a dataset?

A. Lineage view
B. Performance Analyzer
C. Impact analysis
D. DAX Studio

Question 22 (Multi-Select)

Which actions reduce data duplication in Fabric? (Choose 2)

A. Shortcuts
B. Import mode only
C. Shared semantic models
D. Calculated tables
E. Composite models

Question 23 (Single Choice)

Which Fabric artifact is best for structured reporting with high concurrency?

A. Lakehouse
B. Warehouse
C. Eventhouse
D. Dataflow Gen2

Question 24 (Single Choice)

Which file format is recommended for sharing a Power BI report without data?

A. PBIX
B. CSV
C. PBIT
D. PBIP

Section B – Semantic Models (25–48)

Question 25 (Single Choice)

Which storage mode offers the fastest query performance?

A. DirectQuery
B. Direct Lake
C. Import
D. Composite

Question 26 (Single Choice)

When should you use a bridge table?

A. One-to-many relationships
B. Many-to-many relationships
C. One-to-one relationships
D. Hierarchical dimensions

Question 27 (Multi-Select)

What are characteristics of composite models? (Choose 2)

A. Mix Import and DirectQuery
B. Enable aggregations
C. Require XMLA write access
D. Eliminate refresh needs
E. Only supported in Premium

Question 28 (Single Choice)

Which DAX function changes filter context?

A. SUM
B. AVERAGE
C. CALCULATE
D. COUNT

Question 29 (Single Choice)

Which feature allows users to dynamically switch measures in visuals?

A. Calculation groups
B. Field parameters
C. Perspectives
D. Drillthrough

Question 30 (Single Choice)

Which DAX pattern is least performant?

A. SUM
B. SUMX over large tables
C. COUNT
D. DISTINCTCOUNT on low cardinality

Question 31 (Multi-Select)

Which improve DAX performance? (Choose 2)

A. Reduce cardinality
B. Use variables
C. Increase calculated columns
D. Use iterators everywhere
E. Disable relationships

Question 32 (Single Choice)

What is the primary purpose of calculation groups?

A. Reduce model size
B. Apply calculations dynamically
C. Create new tables
D. Improve refresh speed

Question 33 (Single Choice)

Which tool helps identify slow visuals?

A. DAX Studio
B. SQL Profiler
C. Performance Analyzer
D. Lineage view

Question 34 (Single Choice)

Which storage mode supports fallback behavior?

A. Import
B. DirectQuery
C. Direct Lake
D. Composite

Question 35 (Single Choice)

Which feature supports version control of semantic models?

A. Deployment pipelines
B. Endorsement
C. Git integration
D. Sensitivity labels

Question 36 (Matching)

Match the DAX function to its category:

Function	Category
1. FILTER	A. Aggregation
2. SUMX	B. Iterator
3. SELECTEDVALUE	C. Information

Question 37 (Single Choice)

Which table type supports hot and cold partitions?

A. Import
B. DirectQuery
C. Hybrid
D. Calculated

Question 38 (Single Choice)

Which relationship direction is recommended in star schemas?

A. Both
B. Single
C. None
D. Many

Question 39 (Multi-Select)

Which actions reduce semantic model size? (Choose 2)

A. Remove unused columns
B. Use integers for keys
C. Increase precision of decimals
D. Add calculated tables
E. Duplicate dimensions

Question 40 (Single Choice)

Which feature allows formatting measures dynamically?

A. Field parameters
B. Dynamic format strings
C. Perspectives
D. Drillthrough

Question 41 (Single Choice)

Which model type allows real-time and cached data together?

A. Import
B. Hybrid
C. DirectQuery
D. Calculated

Question 42 (Fill in the Blank)

Direct Lake queries data stored as __________ tables in __________.

Question 43 (Single Choice)

Which model design supports aggregations with fallback to detail data?

A. Import
B. Composite
C. DirectQuery
D. Calculated

Question 44 (Single Choice)

Which feature resolves many-to-many relationships cleanly?

A. Bi-directional filters
B. Bridge tables
C. Calculated columns
D. Dynamic measures

Question 45 (Single Choice)

Which DAX function returns the current filter context value?

A. VALUES
B. ALL
C. SELECTEDVALUE
D. HASONEVALUE

Question 46 (Multi-Select)

Which scenarios justify large semantic model storage? (Choose 2)

A. Billions of rows
B. Memory limits exceeded
C. Small datasets
D. Few dimensions
E. Simple models

Question 47 (Single Choice)

Which optimization reduces query complexity?

A. Snowflake schemas
B. Denormalization
C. Many-to-many relationships
D. Bi-directional filters

Question 48 (Single Choice)

What determines incremental refresh partition updates?

A. Refresh frequency
B. Date filters
C. Detect data changes
D. Report usage

Section C – Maintain & Govern (49–60)

Question 49 (Single Choice)

Who can configure tenant-level Fabric settings?

A. Workspace Admin
B. Capacity Admin
C. Fabric Admin
D. Contributor

Question 50 (Multi-Select)

Which features support governance? (Choose 2)

A. Sensitivity labels
B. Endorsement
C. Performance Analyzer
D. RLS
E. Field parameters

Question 51 (Single Choice)

Which endorsement indicates organization-wide trust?

A. Certified
B. Promoted
C. Shared
D. Published

Question 52 (Single Choice)

Which deployment stage is used for validation?

A. Development
B. Test
C. Production
D. Workspace

Question 53 (Single Choice)

Which permission allows modifying a semantic model?

A. Viewer
B. Contributor
C. Admin
D. Reader

Question 54 (Single Choice)

Which feature shows affected reports when changing a model?

A. Lineage view
B. Impact analysis
C. Deployment rules
D. Git history

Question 55 (Multi-Select)

Which actions improve security? (Choose 2)

A. Row-level security
B. Object-level security
C. Calculated columns
D. Field parameters
E. Dynamic measures

Question 56 (Single Choice)

Who can delete a Fabric workspace?

A. Member
B. Contributor
C. Admin
D. Viewer

Question 57 (Fill in the Blank)

Restricting rows based on user identity is called __________ security.

Question 58 (Single Choice)

Which format enables source control–friendly Power BI projects?

A. PBIX
B. PBIP
C. PBIT
D. CSV

Question 59 (Single Choice)

Which feature classifies data sensitivity?

A. Endorsement
B. Sensitivity labels
C. RLS
D. Deployment pipelines

Question 60 (Single Choice)

Which feature supports controlled promotion between environments?

A. Git integration
B. Lineage view
C. Deployment pipelines
D. Shortcuts

✅ ANSWER KEY WITH EXPLANATIONS

(Concise explanations provided; incorrect options explained where relevant)

1. C – Dataflow Gen2

Low-code ingestion and transformation for semi-structured data.

2. A, C

Power Query handles data cleansing and type conversion.

3. C – Shortcut

References data without duplication.

4. C

OneLake is a single logical data lake.

5.

1 → C
2 → B
3 → A

6. C – KQL

Optimized for time-series and telemetry.

7. C

Fuzzy matching breaks query folding.

8. A, C

9. C – Parquet

Optimized for columnar analytics.

10.

RangeStart, RangeEnd

11. C

Aggregation during ingestion reduces model size.

12. A, C

13. C

Calculated columns increase memory usage.

14. C – Lineage view

15. B

16. C – Lakehouse

17. A, D

18. B – SQL

19. B – Lakehouse

20. B – Type 2 SCD

21. C – Impact analysis

22. A, C

23. B – Warehouse

24. C – PBIT

25. C – Import

26. B

27. A, B

28. C – CALCULATE

29. B – Field parameters

30. B

Iterators over large tables are expensive.

31. A, B

32. B

33. C – Performance Analyzer

34. C – Direct Lake

35. C – Git integration

36.

1 → A
2 → B
3 → C

37. C – Hybrid

38. B – Single

39. A, B

40. B – Dynamic format strings

41. B – Hybrid

42.

Delta tables in OneLake

43. B – Composite

44. B

45. C

46. A, B

47. B – Denormalization

48. C

49. C – Fabric Admin

50. A, B

51. A – Certified

52. B – Test

53. C – Admin

54. B – Impact analysis

55. A, B

56. C – Admin

57.

Row-level