vuthanhdatt's Second Brain

Associate-DEA-C01_39

13 min read

Questions and Answers

Question SzadKFLfb5b1S658kDok

Question

A company uses Amazon EMR as an extract, transform, and load (ETL) pipeline to transform data that comes from multiple sources. A data engineer must orchestrate the pipeline to maximize performance.

Which AWS service will meet this requirement MOST cost effectively?

Choices

  • A: Amazon EventBridge
  • B: Amazon Managed Workflows for Apache Airflow (Amazon MWAA)
  • C: AWS Step Functions
  • D: AWS Glue Workflows

Question 9KEyo1OeYMdXLmlbCDMM

Question

An online retail company stores Application Load Balancer (ALB) access logs in an Amazon S3 bucket. The company wants to use Amazon Athena to query the logs to analyze traffic patterns.

A data engineer creates an unpartitioned table in Athena. As the amount of the data gradually increases, the response time for queries also increases. The data engineer wants to improve the query performance in Athena.

Which solution will meet these requirements with the LEAST operational effort?

Choices

  • A: Create an AWS Glue job that determines the schema of all ALB access logs and writes the partition metadata to AWS Glue Data Catalog.
  • B: Create an AWS Glue crawler that includes a classifier that determines the schema of all ALB access logs and writes the partition metadata to AWS Glue Data Catalog.
  • C: Create an AWS Lambda function to transform all ALB access logs. Save the results to Amazon S3 in Apache Parquet format. Partition the metadata. Use Athena to query the transformed data.
  • D: Use Apache Hive to create bucketed tables. Use an AWS Lambda function to transform all ALB access logs.

Question D3XBg1g4cPunXac7Mmm5

Question

A company has a business intelligence platform on AWS. The company uses an AWS Storage Gateway Amazon S3 File Gateway to transfer files from the company’s on-premises environment to an Amazon S3 bucket.

A data engineer needs to setup a process that will automatically launch an AWS Glue workflow to run a series of AWS Glue jobs when each file transfer finishes successfully.

Which solution will meet these requirements with the LEAST operational overhead?

Choices

  • A: Determine when the file transfers usually finish based on previous successful file transfers. Set up an Amazon EventBridge scheduled event to initiate the AWS Glue jobs at that time of day.
  • B: Set up an Amazon EventBridge event that initiates the AWS Glue workflow after every successful S3 File Gateway file transfer event.
  • C: Set up an on-demand AWS Glue workflow so that the data engineer can start the AWS Glue workflow when each file transfer is complete.
  • D: Set up an AWS Lambda function that will invoke the AWS Glue Workflow. Set up an event for the creation of an S3 object as a trigger for the Lambda function.

Question qs0SfxzxHTOyetBSxoCb

Question

A retail company uses Amazon Aurora PostgreSQL to process and store live transactional data. The company uses an Amazon Redshift cluster for a data warehouse.

An extract, transform, and load (ETL) job runs every morning to update the Redshift cluster with new data from the PostgreSQL database. The company has grown rapidly and needs to cost optimize the Redshift cluster.

A data engineer needs to create a solution to archive historical data. The data engineer must be able to run analytics queries that effectively combine data from live transactional data in PostgreSQL, current data in Redshift, and archived historical data. The solution must keep only the most recent 15 months of data in Amazon Redshift to reduce costs.

Which combination of steps will meet these requirements? (Choose two.)

Choices

  • A: Configure the Amazon Redshift Federated Query feature to query live transactional data that is in the PostgreSQL database.
  • B: Configure Amazon Redshift Spectrum to query live transactional data that is in the PostgreSQL database.
  • C: Schedule a monthly job to copy data that is older than 15 months to Amazon S3 by using the UNLOAD command. Delete the old data from the Redshift cluster. Configure Amazon Redshift Spectrum to access historical data in Amazon S3.
  • D: Schedule a monthly job to copy data that is older than 15 months to Amazon S3 Glacier Flexible Retrieval by using the UNLOAD command. Delete the old data from the Redshift cluster. Configure Redshift Spectrum to access historical data from S3 Glacier Flexible Retrieval.
  • E: Create a materialized view in Amazon Redshift that combines live, current, and historical data from different sources.

Question 9Mnl748IBDSbnORjNFvG

Question

A manufacturing company has many IoT devices in facilities around the world. The company uses Amazon Kinesis Data Streams to collect data from the devices. The data includes device ID, capture date, measurement type, measurement value, and facility ID. The company uses facility ID as the partition key.

The company’s operations team recently observed many WriteThroughputExceeded exceptions. The operations team found that some shards were heavily used but other shards were generally idle.

How should the company resolve the issues that the operations team observed?

Choices

  • A: Change the partition key from facility ID to a randomly generated key.
  • B: Increase the number of shards.
  • C: Archive the data on the producer’s side.
  • D: Change the partition key from facility ID to capture date.

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