Azure Data Engineering Essentials

Azure Data Engineering Essentials

University

15 Qs

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Azure Data Engineering Essentials

Azure Data Engineering Essentials

Assessment

Quiz

Information Technology (IT)

University

Practice Problem

Easy

Created by

Titos Junior Shoko

Used 1+ times

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15 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary purpose of Azure Synapse Analytics?

To manage virtual machines and cloud infrastructure.

To provide integrated analytics services for big data and data warehousing.

To provide a platform for web hosting services.

To store large amounts of unstructured data.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How do serverless SQL pools in Azure Synapse differ from provisioned SQL pools?

Serverless SQL pools can only be used for small datasets.

Serverless SQL pools are on-demand and do not require resource provisioning, while provisioned SQL pools require pre-allocated resources.

Provisioned SQL pools are only available in the Azure cloud.

Serverless SQL pools require a fixed amount of resources at all times.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the key components of data engineering on Azure?

Azure Virtual Machines

Key components of data engineering on Azure include Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Blob Storage, and Azure Stream Analytics.

Azure Active Directory

Azure Machine Learning

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Explain the role of Apache Spark in Azure Synapse.

Apache Spark is a storage solution for Azure Synapse.

Apache Spark only supports SQL queries in Azure Synapse.

Apache Spark is used for web hosting in Azure Synapse.

Apache Spark enables big data processing and analytics within Azure Synapse.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What types of data can be processed using Azure Synapse serverless SQL pools?

Data in XML format

Data from SQL Server databases

Data in formats like CSV, Parquet, JSON, ORC, and data from Azure Data Lake Storage.

Data in Excel spreadsheets

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Describe the process of building data analytics solutions in Azure.

The process includes defining requirements, selecting Azure services, ingesting data, transforming it, analyzing, and monitoring the solution.

Ignoring data security and compliance requirements

Using only Power BI for visualization

Collecting data from on-premises servers only

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the significance of data lakes in Azure data engineering?

Data lakes in Azure enable scalable storage and analysis of diverse data types, supporting advanced analytics and machine learning.

Data lakes in Azure do not support machine learning capabilities.

Data lakes in Azure are primarily used for real-time data processing only.

Data lakes in Azure are limited to structured data storage.

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