Question 1
You need to ingest data from an on-premises SQL Server database into a Microsoft Fabric Lakehouse on a daily schedule.
Which Fabric component should you use?
A. Eventstream
B. Data Pipeline
C. KQL Queryset
D. Semantic Model
Answer: B
Explanation
Data Pipelines are designed for orchestrating and scheduling data movement and transformation activities. Eventstreams are intended for streaming data rather than scheduled batch ingestion.
Question 2
You are designing a medallion architecture in a Fabric Lakehouse.
Match each layer to its primary purpose.
| Layer | Purpose |
|---|---|
| 1. Bronze | A. Business-ready data |
| 2. Silver | B. Raw ingested data |
| 3. Gold | C. Cleaned and transformed data |
Answer
- 1 → B
- 2 → C
- 3 → A
Explanation
- Bronze stores raw source data.
- Silver stores cleansed and standardized data.
- Gold stores curated business-ready datasets.
Question 3
Which TWO capabilities are provided by Delta Lake tables?
(Choose two.)
A. ACID transactions
B. Schema enforcement
C. XML indexing
D. Star schema generation
Answers: A, B
Explanation
Delta Lake supports ACID transactions, schema enforcement, schema evolution, and time travel. XML indexing and star schema generation are not Delta Lake features.
Question 4
A Fabric Warehouse contains a fact table with 2 billion rows.
Users frequently filter queries by OrderDate.
What should you consider to improve performance?
A. Remove statistics
B. Convert the table to CSV files
C. Use partitioning based on OrderDate
D. Disable Delta support
Answer: C
Explanation
Partitioning on commonly filtered columns reduces data scanning and improves query performance.
Question 5
Fill in the blank.
The Fabric storage layer that provides a unified logical data lake across Fabric workloads is called __________.
Answer
OneLake
Explanation
OneLake serves as the centralized storage layer across Fabric workloads.
Question 6
You need to process IoT telemetry arriving continuously from thousands of sensors.
Which Fabric component is most appropriate?
A. Warehouse
B. Notebook
C. Eventstream
D. Dataflow Gen2
Answer: C
Explanation
Eventstreams are designed specifically for real-time ingestion and routing of streaming events.
Question 7
A notebook performs the following operations:
- Reads Bronze data
- Removes duplicates
- Standardizes formats
- Writes cleaned data
Which medallion layer is being produced?
A. Bronze
B. Silver
C. Gold
D. Semantic
Answer: B
Explanation
Silver layer contains cleansed and transformed data.
Question 8
Which THREE sources can Eventstreams directly ingest from?
(Choose three.)
A. Azure Event Hubs
B. Sample data source
C. Custom application streams
D. Power BI semantic models
Answers: A, B, C
Explanation
Eventstreams support ingestion from Event Hubs, custom streams, Fabric sources, and sample data.
Question 9
You want to create a shortcut in a Lakehouse that references data stored in another Lakehouse without duplicating the data.
What should you use?
A. Mirrored Database
B. Warehouse View
C. OneLake Shortcut
D. Dataflow Gen2
Answer: C
Explanation
OneLake shortcuts provide virtual access to data without physically copying it.
Question 10
Match each workload to the most appropriate language.
| Workload | Language |
|---|---|
| 1. Warehouse queries | A. KQL |
| 2. Eventhouse analytics | B. T-SQL |
| 3. Spark notebook transformations | C. PySpark |
Answer
- 1 → B
- 2 → A
- 3 → C
Explanation
Warehouses use T-SQL, Eventhouses use KQL, and Spark notebooks commonly use PySpark.
Question 11
Which statement about Dataflow Gen2 is correct?
A. It is used only for streaming data.
B. It provides low-code data transformation.
C. It replaces Spark entirely.
D. It requires KQL.
Answer: B
Explanation
Dataflow Gen2 provides a Power Query-based low-code transformation experience.
Question 12
You need to deduplicate customer records during ingestion.
Which Spark function is commonly used?
A. distinct() or dropDuplicates()
B. cache()
C. collect()
D. union()
Answer: A
Explanation
dropDuplicates() and distinct() are standard Spark methods for removing duplicate records.
Question 13
A Fabric Warehouse query is running slowly.
You discover many joins use columns with mismatched data types.
What should you do?
A. Disable indexing
B. Increase storage only
C. Align data types across joined columns
D. Convert all columns to VARCHAR
Answer: C
Explanation
Matching data types allows the optimizer to generate more efficient execution plans.
Question 14
Which TWO benefits are provided by OneLake shortcuts?
(Choose two.)
A. Reduced data duplication
B. Faster networking hardware
C. Centralized access to data
D. Automatic data encryption removal
Answers: A, C
Explanation
Shortcuts minimize data duplication while enabling centralized access.
Question 15
A company wants to analyze clickstream events with second-level latency.
Which Fabric workload is best suited?
A. Eventhouse
B. Warehouse
C. Dataflow Gen2
D. Semantic Model
Answer: A
Explanation
Eventhouse is optimized for real-time analytics and telemetry workloads.
Question 16
Fill in the blank.
The Spark feature used to continuously process incoming streaming data is called Structured __________.
Answer
Streaming
Explanation
Spark Structured Streaming provides scalable stream processing.
Question 17
Which KQL operator is used to aggregate data?
A. join
B. summarize
C. extend
D. where
Answer: B
Explanation
summarize performs aggregation operations.
Question 18
A notebook fails because a referenced Delta table no longer exists.
What category of issue is this?
A. Authentication issue
B. Schema drift issue
C. Missing resource dependency
D. Capacity issue
Answer: C
Explanation
The notebook references an object that no longer exists.
Question 19
You need to schedule a notebook execution every night.
Which Fabric component should orchestrate this process?
A. Eventstream
B. Pipeline
C. Eventhouse
D. Semantic Model
Answer: B
Explanation
Pipelines provide orchestration and scheduling capabilities.
Question 20
Which operation helps compact small Delta files into larger files?
A. VACUUM
B. ANALYZE
C. OPTIMIZE
D. CACHE
Answer: C
Explanation
OPTIMIZE compacts files and improves query performance.
Question 21
A data engineer wants to improve Spark query performance for repeatedly accessed datasets.
Which technique should be used?
A. VACUUM
B. Partition deletion
C. Cache DataFrames
D. Convert to CSV
Answer: C
Explanation
Caching stores frequently accessed data in memory.
Question 22
Select all valid Fabric items.
(Choose three.)
A. Lakehouse
B. Eventhouse
C. Warehouse
D. Azure VM
Answers: A, B, C
Explanation
Lakehouse, Eventhouse, and Warehouse are Fabric items. Azure VM is not.
Question 23
A streaming solution must enrich incoming events with reference data.
Which technology is most appropriate?
A. Structured Streaming
B. PowerPoint
C. Semantic Model Refresh
D. OneLake Shortcut
Answer: A
Explanation
Structured Streaming supports stream-to-static joins for enrichment.
Question 24
Match the monitoring tool to its purpose.
| Tool | Purpose |
|---|---|
| 1. Monitoring Hub | A. View workload execution history |
| 2. Capacity Metrics | B. Analyze capacity utilization |
| 3. Spark Monitoring | C. Diagnose Spark execution |
Answer
- 1 → A
- 2 → B
- 3 → C
Explanation
Each tool focuses on a different operational aspect of Fabric.
Question 25
Which statement about Eventhouse is TRUE?
A. It only supports batch data.
B. It stores data using KQL databases.
C. It replaces OneLake.
D. It cannot query streaming data.
Answer: B
Explanation
Eventhouse uses KQL databases optimized for real-time analytics.
Question 26
A Lakehouse table experiences slow query performance due to excessive small files.
What is the best first action?
A. Delete the table
B. Run OPTIMIZE
C. Remove partitions
D. Disable Delta
Answer: B
Explanation
OPTIMIZE consolidates files and improves query efficiency.
Question 27
A company needs historical tracking of changes to Delta tables.
Which feature provides this capability?
A. Time Travel
B. Direct Lake
C. Eventstream
D. Monitoring Hub
Answer: A
Explanation
Delta Time Travel enables querying previous versions of data.
Question 28
You need to identify why a pipeline failed overnight.
Where should you start?
A. Monitoring Hub execution details
B. Power BI report settings
C. Semantic model relationships
D. Capacity scaling settings
Answer: A
Explanation
Monitoring Hub provides execution history, logs, and failure details.
Question 29
Which TWO actions commonly improve Warehouse query performance?
(Choose two.)
A. Maintain statistics
B. Use partitioning strategically
C. Convert all columns to strings
D. Use SELECT *
Answers: A, B
Explanation
Statistics and partitioning improve optimization and reduce scanning.
Question 30
A company wants Power BI reports to query Lakehouse data with minimal data duplication and high performance.
Which storage mode should be considered first?
A. Import Mode
B. DirectQuery
C. Direct Lake
D. Live Connection to Excel
Answer: C
Explanation
Direct Lake allows Power BI to access OneLake data directly while delivering near-import performance without data duplication.
Go to the DP-700 Exam Prep Hub main page.
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