In this article i am gone to share Introduction to Designing Data Lakes on AWS Week 2 Quiz Answers with you..

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Introduction to Designing Data Lakes on AWS Week 2 Quiz Answers

Question 1)
True or False: AWS Lake Formation is a centralized repository, such as a data lake, that stores structured and unstructured data at any scale.

• True
• False

Question 2)
What is the structure of the AWS Glue Metadata Catalog?

• The AWS Glue Metadata Catalog consists of tables. Each table has a schema, which outlines the structure of a table, including columns, data type definitions, and more. The tables are organized into logical groups that are called databases.
• The AWS Glue Metadata Catalog contains buckets with different types of storage options. AWS Glue Metadata Catalog stores data as objects in these buckets.
• The AWS Glue Metadata Catalog is the storage that is associated with automated database backups and any active database snapshots. It consists of the General Purpose SSD, Provisioned IOPS SSD, Throughput Optimized HDD, and Cold HDD volume types.
• The AWS Glue Metadata Catalog consists of file systems or databases for any applications that require fine, granular updates and access to raw, unformatted, block-level storage.

Question 3)
True or False: Customers can use Amazon API Gateway to ingest real-time data in a RESTful manner through the creation of an HTTP-based API, which acts as the front door or interface to ingestion logic or data lake storage on the backend.

• True
• False

Question 4)
Which statement about AWS Lake Formation is true?

• AWS Lake Formation runs big data frameworks, such as Apache Hadoop.
• AWS Lake Formation deploys, operates, and scales clusters in the AWS Cloud
• AWS Lake Formation ingests, cleanses, and transforms the structured and organized data.
• AWS Lake Formation registers the Amazon Simple Storage Service (Amazon S3) buckets and paths where the data lake will reside.

Question 5)
Which service is commonly used for real-time data processing when Amazon Kinesis Data Streams is used for data ingestion?

• Amazon Kinesis Data Analytics
• Amazon EMR
• Amazon Athena
• AWS Glue Jobs

Question 6)
Apache Hadoop is an open-source framework that is used to efficiently store and process large datasets. A solutions architect is working for a company that currently uses Apache Hadoop on-premises for data processing jobs. The company wants to use AWS for these jobs, but they also want to continue using the same technology. Which service should the solutions architect choose for this use case?

• AWS Lambda
• Amazon EMR
• Amazon OpenSearch Service
• Amazon Kinesis Data Analytics

Question 7)
A team of machine learning (ML) experts are working for a company. The company wants to use the data in their data lake to train an ML model that they create. The company wants the most control that they can have over this model and the environment that it is trained in. Which AWS ML approach should the team take?

• Use a pretrained model from an AWS service, such as Amazon Rekognition.
• Launch an Amazon Elastic Compute Cloud (Amazon EC2) instance by using an AWS Deep Learning Amazon Machine Image (AMI) to host the application that will train the model.
• Launch an Amazon Elastic Compute Cloud (Amazon EC2) instance and run Amazon SageMaker on it to train the model.
• Create an AWS Lambda function with the training logic in the handler, and run the training based on an event.

Question 8)
A solutions architect needs to process and analyze data as it is ingested into a data lake in real time. They want to get timely insights about the streaming data. Which service should the solutions architect use for this use case?

• Amazon API Gateway
• Amazon EMR
• Amazon Kinesis
• AWS Lambda

Question 9)
Which services can query data that is needed to build reports? (Choose TWO.)

• Amazon Athena
• AWS Lambda
• Amazon Glue
• Amazon Redshift
• Amazon Elastic Compute Cloud