| Exam Code | Data-Engineer-Associate |
| Exam Name | AWS Certified Data Engineer - Associate (DEA-C01) |
| Questions | 80 |
| Update Date | October 10,2024 |
| Price |
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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.
Answer: B,D
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.
Answer: B
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.
Answer: B
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.
Answer: D
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.
Answer: B
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