2.8 Introduction to Azure Databricks

Question 1

What is Azure Databricks primarily used for?

a) Data storage

b) Data exploration and cleanup

c) Data analysis and reporting

d) Data security

Answer 1

b) Data exploration and cleanup

Question 2

What technology does Azure Databricks use under the hood?

a) Apache Hadoop

b) Apache Kafka

c) Apache Spark

d) Apache Cassandra

Answer 2

c) Apache Spark

Question 3

What advantage does Azure Databricks offer in terms of scalability?

a) Ability to spin up and down clusters as needed

b) Ability to store unlimited amounts of data

c) Ability to integrate with any data source

d) Ability to perform real-time data analysis

Answer 3

a) Ability to spin up and down clusters as needed

Question 4

What configuration options are available when creating an Azure Databricks cluster?

a) Size of clusters, number of nodes, and CPU/RAM specifications

b) Type of data sources, data formats, and data transformations

c) Pricing tier, data retention policies, and access controls

d) Backup and disaster recovery options, data encryption, and compliance settings

Answer 4

a) Size of clusters, number of nodes, and CPU/RAM specifications

Question 5

How is Azure Databricks priced?

a) Pay-as-you-go based on the number of users

b) Flat monthly fee based on the size of the cluster

c) Pay-as-you-go based on the amount of data processed

d) Free with limited features, with optional premium plans available

Answer 5

c) Pay-as-you-go based on the amount of data processed

Question 6

What is the benefit of using Azure Databricks for data analysis?

a) Real-time data analysis capabilities

b) Seamless integration with Azure Storage Accounts

c) Support for both structured and unstructured data

d) Ability to automate data exploration and cleanup

Answer 6

d) Ability to automate data exploration and cleanup