Question 1
You need to provide data engineers access to create Lakehouses and Data Warehouses within a Fabric workspace. However, they should not be able to manage workspace permissions.
Which workspace role should you assign?
A. Viewer
B. Contributor
C. Member
D. Admin
Answer: C
Explanation
Members can create and manage content within a workspace but cannot perform all administrative functions available to Admins.
- A is incorrect because Viewers have read-only access.
- B is incorrect because Contributors cannot manage all workspace content ownership scenarios.
- C is correct.
- D is incorrect because Admin grants excessive permissions.
Question 2
You are implementing a Medallion architecture.
Match each layer to its primary purpose.
| Layer | Purpose |
|---|---|
| 1. Bronze | A. Business-ready curated data |
| 2. Silver | B. Raw ingested data |
| 3. Gold | C. Cleansed and validated data |
Answer
- 1 → B
- 2 → C
- 3 → A
Explanation
Bronze stores raw data, Silver contains cleansed and transformed data, and Gold provides analytics-ready datasets.
Question 3
A Fabric Eventstream receives telemetry from 50,000 IoT devices.
You need to route the incoming events to multiple destinations simultaneously.
Which feature should you use?
A. Dataflow Gen2
B. Eventstream routing
C. Notebook scheduling
D. Warehouse shortcuts
Answer: B
Explanation
Eventstreams can route a single event stream to multiple destinations.
Question 4
Select TWO answers.
Which destinations can Eventstreams write to directly?
A. Eventhouse
B. Lakehouse
C. SQL Database
D. Notebook
E. Activator
Answer: A, E
Explanation
Common Eventstream destinations include:
- Eventhouse
- Activator
- Lakehouse
- KQL Database
Notebook is not a direct destination.
Question 5
Fill in the blank.
A OneLake shortcut allows users to access data without creating a physical __________ of the data.
Answer
Copy
Explanation
Shortcuts create logical references to data rather than duplicating storage.
Question 6
A Fabric notebook processing job frequently fails due to insufficient executor resources.
What should you do first?
A. Increase notebook timeout
B. Rebuild the Lakehouse
C. Scale Spark resources
D. Delete checkpoints
Answer: C
Explanation
Resource shortages are typically addressed by increasing Spark capacity or executor allocation.
Question 7
You are designing a real-time analytics solution.
Requirements:
- Ingest millions of events per minute
- Sub-second querying
- Time-series analysis
Which technology is most appropriate?
A. Dataflow Gen2
B. Eventhouse
C. Warehouse
D. Semantic Model
Answer: B
Explanation
Eventhouse is optimized for high-volume streaming analytics and KQL workloads.
Question 8
Which KQL operator is used to aggregate records?
A. project
B. where
C. extend
D. summarize
Answer: D
Explanation
The summarize operator performs aggregations such as count(), avg(), and sum().
Question 9
A Dataflow Gen2 refresh suddenly begins failing after a source schema change.
What is the most likely cause?
A. Workspace permissions
B. Network latency
C. Column mismatch
D. Spark pool scaling
Answer: C
Explanation
Schema changes commonly cause transformation failures when expected columns are missing or renamed.
Question 10
Select THREE answers.
Which actions help improve Delta table performance?
A. OPTIMIZE
B. V-Order
C. Small file generation
D. Compaction
E. Disabling partitioning
Answer: A, B, D
Explanation
OPTIMIZE, V-Order, and compaction improve query efficiency and storage organization.
Question 11
You need to monitor Fabric pipeline execution history.
Where should you start?
A. Capacity Metrics App
B. Pipeline monitoring pane
C. Purview Hub
D. Semantic model settings
Answer: B
Explanation
Pipeline monitoring provides execution status, duration, and error details.
Question 12
A streaming solution requires SQL-like processing over continuously arriving data.
Which option should you choose?
A. Data Factory
B. Eventstream
C. Warehouse stored procedures
D. Power BI Report
Answer: B
Explanation
Eventstreams support real-time stream processing and routing.
Question 13
Match the technology to its primary purpose.
| Technology | Purpose |
|---|---|
| 1. Eventhouse | A. Batch orchestration |
| 2. Pipeline | B. Real-time analytics |
| 3. Notebook | C. Spark processing |
Answer
- 1 → B
- 2 → A
- 3 → C
Question 14
You need to reduce query latency against large Delta tables.
Which strategy is most effective?
A. Increase report refresh frequency
B. Create more workspaces
C. Enable V-Order optimization
D. Disable partitioning
Answer: C
Explanation
V-Order reorganizes storage to improve analytical query performance.
Question 15
A warehouse query scans billions of rows unnecessarily.
What should you investigate first?
A. Query filters
B. Workspace permissions
C. Capacity region
D. Semantic model ownership
Answer: A
Explanation
Missing predicates often cause excessive data scans.
Question 16
Select TWO answers.
Which items can be sources for OneLake shortcuts?
A. ADLS Gen2
B. Amazon S3
C. Power BI Report
D. Notebook
Answer: A, B
Explanation
Shortcuts commonly connect to ADLS Gen2 and Amazon S3 data.
Question 17
Fill in the blank.
Spark Structured Streaming processes data using incremental __________.
Answer
Micro-batches
Explanation
Structured Streaming generally operates through continuous micro-batch execution.
Question 18
A Fabric capacity consistently shows high CU utilization.
What should you do?
A. Delete semantic models
B. Reduce storage
C. Review workload consumption patterns
D. Disable monitoring
Answer: C
Explanation
Investigating workload usage is the first step before scaling or optimization.
Question 19
Which KQL function is commonly used to create time windows?
A. datetime_diff()
B. bin()
C. tostring()
D. strcat()
Answer: B
Explanation
bin() groups timestamps into fixed intervals for windowed analysis.
Question 20
You need to process late-arriving streaming events.
Which concept should be configured?
A. Watermarking
B. Capacity scaling
C. Workspace role assignment
D. Notebook scheduling
Answer: A
Explanation
Watermarks help define how late data should be handled.
Question 21
A notebook execution fails with a Python module import error.
What is the most likely cause?
A. Missing package dependency
B. Lakehouse corruption
C. Capacity throttling
D. Semantic model refresh issue
Answer: A
Explanation
Import failures typically indicate missing libraries.
Question 22
Select THREE answers.
Which metrics are useful when monitoring data ingestion?
A. Throughput
B. Latency
C. Failure rate
D. Workspace color theme
E. Event volume
Answer: A, B, C
Explanation
Throughput, latency, and failures are key ingestion health indicators.
Question 23
You want to accelerate analytical queries against external data accessed through shortcuts.
Which feature should you consider?
A. Semantic Links
B. Query Acceleration
C. Spark Monitoring
D. Activator
Answer: B
Explanation
Query Acceleration improves performance when querying external shortcut data.
Question 24
A pipeline contains five independent activities.
How can you reduce overall execution time?
A. Execute activities sequentially
B. Disable retries
C. Run activities in parallel
D. Convert activities to reports
Answer: C
Explanation
Independent tasks should execute concurrently whenever possible.
Question 25
Match the optimization technique to its purpose.
| Technique | Purpose |
|---|---|
| 1. Partitioning | A. Reduce file count |
| 2. Compaction | B. Improve data pruning |
| 3. Caching | C. Reduce repeated reads |
Answer
- 1 → B
- 2 → A
- 3 → C
Question 26
Which Fabric component is best suited for orchestration of complex ETL workflows?
A. Eventhouse
B. Data Pipeline
C. Semantic Model
D. Activator
Answer: B
Explanation
Pipelines coordinate and orchestrate end-to-end workflows.
Question 27
A real-time dashboard requires alerts when sensor temperature exceeds a threshold.
Which Fabric capability is most appropriate?
A. Activator
B. Warehouse
C. Notebook
D. V-Order
Answer: A
Explanation
Activator enables event-driven actions and alerts.
Question 28
Select TWO answers.
Which actions commonly improve Spark job performance?
A. Reduce shuffle operations
B. Use broadcast joins when appropriate
C. Increase small file generation
D. Disable partition pruning
Answer: A, B
Explanation
Reducing shuffles and using broadcast joins can significantly improve Spark efficiency.
Question 29
A warehouse workload contains many repeated analytical queries.
Which optimization is most likely to help?
A. Remove statistics
B. Increase file fragmentation
C. Use result caching
D. Disable parallelism
Answer: C
Explanation
Result caching can dramatically improve repeated query performance.
Question 30
A data engineering team must investigate intermittent Eventstream ingestion failures.
What should be reviewed first?
A. Report visualizations
B. Eventstream monitoring and diagnostics
C. Semantic model relationships
D. Workspace themes
Answer: B
Explanation
Eventstream diagnostics provide details about ingestion health, routing issues, throughput bottlenecks, and destination errors, making them the best starting point for troubleshooting.
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