Introduction to Designing Data Lakes on AWS Week 1 Quiz

Course Name: Introduction to Designing Data Lakes on AWS (AWS Cloud Solutions Architect)

Course Link: Introduction to Designing Data Lakes on AWS

These are Introduction to Designing Data Lakes on AWS Week 1 Quiz Answers

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Question 1
What is the main value proposition of data lakes?
The ability to store user-generated data, such as data from antennas and sensors.
The ability to define the data schema before ingesting and storing data.
The ability to ingest and store data that could be the answer for future questions when they are processed with the correct data processing mechanisms.
The ability to combine multiple databases together to expand their capacity and availability.

Answer: The ability to ingest and store data that could be the answer for future questions when they are processed with the correct data processing mechanisms.

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Question 2
True or False: Two of the fundamental components of data lakes are data catalog and search.
True
False

Answer: True

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These are Introduction to Designing Data Lakes on AWS Week 1 Quiz Answers

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Question 3
A company sorts and structures data before entering information into a database. They also store unstructured data in another storage location. These two data locations are siloed from each other. How can the company benefit from using a data lake?
Data lakes mostly process data after it has been stored in the cloud or on-premises.
A data lake provides the most secure way to store data in the AWS Cloud.
With a data lake, a company can store structured and unstructured data at virtually any scale.
A data lake is a direct replacement of a data warehouse.

Answer: With a data lake, a company can store structured and unstructured data at virtually any scale.

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These are Introduction to Designing Data Lakes on AWS Week 1 Quiz Answers

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Question 4
Which statements about data lakes and data warehouses are true? (Choose TWO.)
Data lakes use schema-on-write architectures and data warehouses use schema-on-read architectures.
Data lakes offer more choices in terms of the technology that is used for processing data. In contrast, data warehouses are more restricted to using Structured Query Language (SQL) as the query technology.
The solutions architect can combine both data lakes and data warehouses to better extract insights and turn data into information.
The solutions architect cannot attach data visualization tools to data warehouses.
Data lakes are not future-proof, which means that they must be reconfigured each time new data is ingested.

Answer:
Data lakes offer more choices in terms of the technology that is used for processing data. In contrast, data warehouses are more restricted to using Structured Query Language (SQL) as the query technology.
The solutions architect can combine both data lakes and data warehouses to better extract insights and turn data into information.

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These are Introduction to Designing Data Lakes on AWS Week 1 Quiz Answers

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Question 5
True or False: Data lakes integrate with analytics tools that can help companies eliminate costly and complex extract, transform, and load (ETL) processes.
True
False

Answer: True

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Question 6
Which term indicates that a data lake lacks curation, management, cataloging, lifecycle or retention policies, and metadata?
Data swamp
Data warehouse
Data catalog
Database

Answer: Data swamp

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These are Introduction to Designing Data Lakes on AWS Week 1 Quiz Answers

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Question 7
Which service can be used to run simple queries against data in a data lake?
Amazon Kinesis Data Firehose
Amazon Simple Storage Service (Amazon S3)
Amazon Kinesis Agent
Amazon Athena

Answer: Amazon Athena

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These are Introduction to Designing Data Lakes on AWS Week 1 Quiz Answers

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