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Amazon Data-Engineer-Associate Dumps

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Exam Code Data-Engineer-Associate
Exam Name AWS Certified Data Engineer - Associate (DEA-C01)
Update Date 20 May, 2024
Total Questions 80 Questions Answers With Explanation
$75

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Question # 1

A company has five offices in different AWS Regions. Each office has its own humanresources (HR) department that uses a unique IAM role. The company stores employeerecords in a data lake that is based on Amazon S3 storage. A data engineering team needs to limit access to the records. Each HR department shouldbe able to access records for only employees who are within the HR department's Region.Which combination of steps should the data engineering team take to meet thisrequirement with the LEAST operational overhead? (Choose two.)

A. Use data filters for each Region to register the S3 paths as data locations.
B. Register the S3 path as an AWS Lake Formation location.
C. Modify the IAM roles of the HR departments to add a data filter for each department'sRegion.
D. Enable fine-grained access control in AWS Lake Formation. Add a data filter for eachRegion.
E. Create a separate S3 bucket for each Region. Configure an IAM policy to allow S3access. Restrict access based on Region.

Question # 2

A healthcare company uses Amazon Kinesis Data Streams to stream real-time health datafrom wearable devices, hospital equipment, and patient records.A data engineer needs to find a solution to process the streaming data. The data engineerneeds to store the data in an Amazon Redshift Serverless warehouse. The solution must support near real-time analytics of the streaming data and the previous day's data.Which solution will meet these requirements with the LEAST operational overhead?

A. Load data into Amazon Kinesis Data Firehose. Load the data into Amazon Redshift.
B. Use the streaming ingestion feature of Amazon Redshift.
C. Load the data into Amazon S3. Use the COPY command to load the data into AmazonRedshift.
D. Use the Amazon Aurora zero-ETL integration with Amazon Redshift.

Question # 3

A company is migrating a legacy application to an Amazon S3 based data lake. A dataengineer reviewed data that is associated with the legacy application. The data engineerfound that the legacy data contained some duplicate information.The data engineer must identify and remove duplicate information from the legacyapplication data.Which solution will meet these requirements with the LEAST operational overhead?

A. Write a custom extract, transform, and load (ETL) job in Python. Use theDataFramedrop duplicatesf) function by importingthe Pandas library to perform datadeduplication.
B. Write an AWS Glue extract, transform, and load (ETL) job. Usethe FindMatchesmachine learning(ML) transform to transform the data to perform data deduplication.
C. Write a custom extract, transform, and load (ETL) job in Python. Import the Pythondedupe library. Use the dedupe library to perform data deduplication.
D. Write an AWS Glue extract, transform, and load (ETL) job. Import the Python dedupelibrary. Use the dedupe library to perform data deduplication.

Question # 4

A company needs to build a data lake in AWS. The company must provide row-level dataaccess and column-level data access to specific teams. The teams will access the data byusing Amazon Athena, Amazon Redshift Spectrum, and Apache Hive from Amazon EMR.Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon S3 for data lake storage. Use S3 access policies to restrict data access byrows and columns. Provide data access throughAmazon S3.
B. Use Amazon S3 for data lake storage. Use Apache Ranger through Amazon EMR torestrict data access byrows and columns. Providedata access by using Apache Pig.
C. Use Amazon Redshift for data lake storage. Use Redshift security policies to restrictdata access byrows and columns. Provide data accessby usingApache Spark and AmazonAthena federated queries.
D. UseAmazon S3 for data lake storage. Use AWS Lake Formation to restrict data accessby rows and columns. Provide data access through AWS Lake Formation.

Question # 5

A company uses an Amazon Redshift provisioned cluster as its database. The Redshiftcluster has five reserved ra3.4xlarge nodes and uses key distribution.A data engineer notices that one of the nodes frequently has a CPU load over 90%. SQLQueries that run on the node are queued. The other four nodes usually have a CPU loadunder 15% during daily operations.The data engineer wants to maintain the current number of compute nodes. The dataengineer also wants to balance the load more evenly across all five compute nodes.Which solution will meet these requirements?

A. Change the sort key to be the data column that is most often used in a WHERE clauseof the SQL SELECT statement.
B. Change the distribution key to the table column that has the largest dimension.
C. Upgrade the reserved node from ra3.4xlarqe to ra3.16xlarqe.
D. Change the primary key to be the data column that is most often used in a WHEREclause of the SQL SELECT statement.

Question # 6

A company is developing an application that runs on Amazon EC2 instances. Currently, thedata that the application generates is temporary. However, the company needs to persistthe data, even if the EC2 instances are terminated.A data engineer must launch new EC2 instances from an Amazon Machine Image (AMI)and configure the instances to preserve the data.Which solution will meet this requirement?

A. Launch new EC2 instances by using an AMI that is backed by an EC2 instance storevolume that contains the application data. Apply the default settings to the EC2 instances.
B. Launch new EC2 instances by using an AMI that is backed by a root Amazon ElasticBlock Store (Amazon EBS) volume that contains the application data. Apply the defaultsettings to the EC2 instances.
C. Launch new EC2 instances by using an AMI that is backed by an EC2 instance storevolume. Attach an Amazon Elastic Block Store (Amazon EBS) volume to contain theapplication data. Apply the default settings to the EC2 instances.
D. Launch new EC2 instances by using an AMI that is backed by an Amazon Elastic BlockStore (Amazon EBS) volume. Attach an additional EC2 instance store volume to containthe application data. Apply the default settings to the EC2 instances.

Question # 7

A data engineer must ingest a source of structured data that is in .csv format into anAmazon S3 data lake. The .csv files contain 15 columns. Data analysts need to runAmazon Athena queries on one or two columns of the dataset. The data analysts rarelyquery the entire file.Which solution will meet these requirements MOST cost-effectively?

A. Use an AWS Glue PySpark job to ingest the source data into the data lake in .csvformat.
B. Create an AWS Glue extract, transform, and load (ETL) job to read from the .csvstructured data source. Configure the job to ingest the data into the data lake in JSONformat.C. Use an AWS Glue PySpark job to ingest the source data into the data lake in ApacheAvro format.
D. Create an AWS Glue extract, transform, and load (ETL) job to read from the .csvstructured data source. Configure the job to write the data into the data lake in ApacheParquet format.

Question # 8

A data engineer uses Amazon Redshift to run resource-intensive analytics processes onceevery month. Every month, the data engineer creates a new Redshift provisioned cluster.The data engineer deletes the Redshift provisioned cluster after the analytics processesare complete every month. Before the data engineer deletes the cluster each month, thedata engineer unloads backup data from the cluster to an Amazon S3 bucket.The data engineer needs a solution to run the monthly analytics processes that does notrequire the data engineer to manage the infrastructure manually.Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon Step Functions to pause the Redshift cluster when the analytics processesare complete and to resume the cluster to run new processes every month.
B. Use Amazon Redshift Serverless to automatically process the analytics workload.
C. Use the AWS CLI to automatically process the analytics workload.
D. Use AWS CloudFormation templates to automatically process the analytics workload.

Question # 9

A financial company wants to use Amazon Athena to run on-demand SQL queries on apetabyte-scale dataset to support a business intelligence (BI) application. An AWS Glue jobthat runs during non-business hours updates the dataset once every day. The BIapplication has a standard data refresh frequency of 1 hour to comply with companypolicies. A data engineer wants to cost optimize the company's use of Amazon Athena withoutadding any additional infrastructure costs.Which solution will meet these requirements with the LEAST operational overhead?

A. Configure an Amazon S3 Lifecycle policy to move data to the S3 Glacier Deep Archivestorage class after 1 day
B. Use the query result reuse feature of Amazon Athena for the SQL queries.
C. Add an Amazon ElastiCache cluster between the Bl application and Athena.
D. Change the format of the files that are in the dataset to Apache Parquet.

Question # 10

A company uses an Amazon Redshift cluster that runs on RA3 nodes. The company wantsto scale read and write capacity to meet demand. A data engineer needs to identify asolution that will turn on concurrency scaling.Which solution will meet this requirement?

A. Turn on concurrency scaling in workload management (WLM) for Redshift Serverlessworkgroups.
B. Turn on concurrency scaling at the workload management (WLM) queue level in theRedshift cluster.
C. Turn on concurrency scaling in the settings duringthe creation of andnew Redshiftcluster.
D. Turn on concurrency scaling for the daily usage quota for the Redshift cluster.