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Azure Synapse Analytics Quiz

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

What is the primary purpose of Synapse SQL in Azure Synapse Analytics?

a)

Data warehousing and query processing

b)

Log analytics

c)

Machine learning model training

d)

Event-driven processing

2.

Which Synapse SQL feature allows querying data without needing to load it into a dedicated SQL pool?

a)

SQL Server Integration

b)

On-demand Querying

c)

Dedicated SQL Pool

d)

Data Streaming

3.

What is Apache Spark primarily used for in Azure Synapse Analytics?

a)

Real-time transactional processing

b)

Big data processing and machine learning

c)

Simple file storage

d)

Static reporting

4.

Which programming languages are supported by Apache Spark in Azure Synapse?

a)

Java, SQL, Rust

b)

Python, Scala, Java

c)

PHP, C++, Swift

d)

Go, TypeScript, Ruby

5.

What is the purpose of Data Explorer in Azure Synapse Analytics?

a)

Managing relational databases

b)

Large-scale log and time-series analysis

c)

File compression and archiving

d)

Transaction handling

6.

Which integration service is built into Azure Synapse Analytics for orchestrating data movement?

a)

SQL Server Management Studio

b)

Azure Data Factory

c)

Event Hub

d)

Hadoop

7.

What type of data can Synapse Link for Cosmos DB process?

a)

Only structured transactional data

b)

Both structured and unstructured data in near real-time

c)

Only JSON files

d)

Compressed datasets

8.

How does Synapse Analytics integrate with Power BI?

a)

Through APIs only

b)

Through direct query connections and data pipelines

c)

Power BI cannot be integrated

d)

Only via file exports

9.

What is the main benefit of using serverless SQL pools in Synapse Analytics?

a)

Requires no resource provisioning

b)

Fixed pricing model

c)

Real-time indexing

d)

Event-driven architecture

10.

What is the recommended storage format for optimized performance in Azure Synapse?

a)

CSV

b)

Parquet

c)

TXT

d)

XML

11.

What is the primary advantage of using Spark pools over dedicated SQL pools?

a)

Scalability in big data processing

b)

Enhanced SQL query optimization

c)

Faster relational database indexing

d)

Improved network security

12.

How can you schedule data pipeline executions in Azure Synapse Analytics?

a)

Using SQL triggers

b)

Using Azure Data Factory scheduling

c)

Using Spark Streaming

d)

Manually only

13.

What Azure Synapse component is best for handling semi-structured and unstructured data?

a)

Dedicated SQL Pools

b)

Spark Pools

c)

Synapse Link

d)

Data Explorer

14.

Which Azure service is commonly used alongside Synapse Analytics for AI-powered insights?

a)

Azure Machine Learning

b)

Microsoft Outlook

c)

Azure Firewall

d)

Blob Storage

15.

What file format is recommended for optimized data processing in Apache Spark within Synapse?

a)

JSON

b)

Parquet

c)

DOCX

d)

HTML

16.

What feature in Synapse Analytics allows querying external data without importing it?

a)

PolyBase

b)

Data Lake Storage

c)

Event Grid

d)

Stream Processing

17.

What is the main benefit of integrating Synapse Analytics with Azure Data Lake?

a)

Efficient storage and retrieval of large datasets

b)

Enhanced database indexing

c)

Real-time data transactions

d)

Improved SQL query processing speed

18.

What tool enables visual data exploration in Synapse Analytics?

a)

Power BI

b)

Event Hub

c)

Azure Kubernetes Service

d)

JSON Explorer

19.

Which execution model is used in Spark within Azure Synapse?

a)

Batch and stream processing

b)

Only batch processing

c)

Only stream processing

d)

Event-driven triggers

20.

What does Synapse Link enable in Azure Synapse Analytics?

a)

Seamless integration with operational databases

b)

SQL query acceleration

c)

Distributed database replication

d)

Server provisioning automation