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Data-Engineer-Associate Practice Questions

AWS Certified Data Engineer - Associate (DEA-C01)

Last Update 4 days ago
Total Questions : 302

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Question # 31

A data engineer configures a large number of AWS Glue jobs that all start up around the same time. All the jobs run for less than 1 hour in the same subnet of the same VP

C.  

All the AWS Glue jobs run on a

G.  

1X worker type.

Some of the jobs occasionally fail with the following error: “The specified subnet does not have enough free addresses to satisfy the request.”

What is the likely root cause of the error?

Options:

A.  

There are not enough IP addresses in the subnet.

B.  

The

G.  

1X worker type cannot access the subnet.

C.  

AWS Glue does not have the correct IAM permissions to add additional IP addresses to the subnet.

D.  

There are not enough IP addresses in the VP

C.  

Discussion 0
Question # 32

A company uses an on-premises Microsoft SQL Server database to store financial transaction data. The company migrates the transaction data from the on-premises database to AWS at the end of each month. The company has noticed that the cost to migrate data from the on-premises database to an Amazon RDS for SQL Server database has increased recently.

The company requires a cost-effective solution to migrate the data to AWS. The solution must cause minimal downtown for the applications that access the database.

Which AWS service should the company use to meet these requirements?

Options:

A.  

AWS Lambda

B.  

AWS Database Migration Service (AWS DMS)

C.  

AWS Direct Connect

D.  

AWS DataSync

Discussion 0
Question # 33

A technology company currently uses Amazon Kinesis Data Streams to collect log data in real time. The company wants to use Amazon Redshift for downstream real-time queries and to enrich the log data.

Which solution will ingest data into Amazon Redshift with the LEAST operational overhead?

Options:

A.  

Set up an Amazon Data Firehose delivery stream to send data to a Redshift provisioned cluster table.

B.  

Set up an Amazon Data Firehose delivery stream to send data to Amazon S3. Configure a Redshift provisioned cluster to load data every minute.

C.  

Configure Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) to send data directly to a Redshift provisioned cluster table.

D.  

Use Amazon Redshift streaming ingestion from Kinesis Data Streams and to present data as a materialized view.

Discussion 0
Question # 34

A transportation company wants to track vehicle movements by capturing geolocation records. The records are 10 bytes in size. The company receives up to 10,000 records every second. Data transmission delays of a few minutes are acceptable because of unreliable network conditions.

The transportation company wants to use Amazon Kinesis Data Streams to ingest the geolocation data. The company needs a reliable mechanism to send data to Kinesis Data Streams. The company needs to maximize the throughput efficiency of the Kinesis shards.

Which solution will meet these requirements in the MOST operationally efficient way?

Options:

A.  

Kinesis Agent

B.  

Kinesis Producer Library (KPL)

C.  

Amazon Data Firehose

D.  

Kinesis SDK

Discussion 0
Question # 35

A retail company stores customer data in an Amazon S3 bucket. Some of the customer data contains personally identifiable information (PII) about customers. The company must not share PII data with business partners.

A data engineer must determine whether a dataset contains PII before making objects in the dataset available to business partners.

Which solution will meet this requirement with the LEAST manual intervention?

Options:

A.  

Configure the S3 bucket and S3 objects to allow access to Amazon Macie. Use automated sensitive data discovery in Macie.

B.  

Configure AWS CloudTrail to monitor S3 PUT operations. Inspect the CloudTrail trails to identify operations that save PII.

C.  

Create an AWS Lambda function to identify PII in S3 objects. Schedule the function to run periodically.

D.  

Create a table in AWS Glue Data Catalog. Write custom SQL queries to identify PII in the table. Use Amazon Athena to run the queries.

Discussion 0
Question # 36

A company is developing a log streaming pipeline that uses Amazon Data Firehose. The pipeline streams Amazon CloudWatch Logs data to an Amazon S3 bucket. The company ' s analytics team needs to use the data in audits. The pipeline must deliver only the relevant logs to the S3 bucket in a compatible format for the team ' s analysis.

Which solution will meet these requirements and maintain reliable performance?

Options:

A.  

Set the S3 bucket rules to allow logs from only specific timestamp ranges. Create an AWS Lambda function that converts the log files to the desired format. Use an S3 trigger to invoke the Lambda function.

B.  

Create a subscription filter in the CloudWatch Logs log group that uses the Firehose delivery stream as the destination. Create an AWS Lambda function that converts the log files to the desired format. Configure Firehose to invoke the Lambda function.

C.  

Create a subscription filter in the CloudWatch Logs log group. Configure the filter to monitor the Firehose stream. Create an AWS Lambda function to convert the log files to the desired format. Configure Firehose to invoke the Lambda function.

D.  

Tag the CloudWatch Logs log groups that the analytics team needs. Configure Firehose to ingest only the tagged log groups. Configure Firehose to write the output in the desired format.

Discussion 0
Question # 37

A financial services company stores financial data in Amazon Redshift. A data engineer wants to run real-time queries on the financial data to support a web-based trading application. The data engineer wants to run the queries from within the trading application.

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

Options:

A.  

Establish WebSocket connections to Amazon Redshift.

B.  

Use the Amazon Redshift Data API.

C.  

Set up Java Database Connectivity (JDBC) connections to Amazon Redshift.

D.  

Store frequently accessed data in Amazon S3. Use Amazon S3 Select to run the queries.

Discussion 0
Question # 38

A company stores server logs in an Amazon 53 bucket. The company needs to keep the logs for 1 year. The logs are not required after 1 year.

A data engineer needs a solution to automatically delete logs that are older than 1 year.

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

Options:

A.  

Define an S3 Lifecycle configuration to delete the logs after 1 year.

B.  

Create an AWS Lambda function to delete the logs after 1 year.

C.  

Schedule a cron job on an Amazon EC2 instance to delete the logs after 1 year.

D.  

Configure an AWS Step Functions state machine to delete the logs after 1 year.

Discussion 0
Question # 39

A company currently stores all of its data in Amazon S3 by using the S3 Standard storage class.

A data engineer examined data access patterns to identify trends. During the first 6 months, most data files are accessed several times each day. Between 6 months and 2 years, most data files are accessed once or twice each month. After 2 years, data files are accessed only once or twice each year.

The data engineer needs to use an S3 Lifecycle policy to develop new data storage rules. The new storage solution must continue to provide high availability.

Which solution will meet these requirements in the MOST cost-effective way?

Options:

A.  

Transition objects to S3 One Zone-Infrequent Access (S3 One Zone-IA) after 6 months. Transfer objects to S3 Glacier Flexible Retrieval after 2 years.

B.  

Transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 6 months. Transfer objects to S3 Glacier Flexible Retrieval after 2 years.

C.  

Transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 6 months. Transfer objects to S3 Glacier Deep Archive after 2 years.

D.  

Transition objects to S3 One Zone-Infrequent Access (S3 One Zone-IA) after 6 months. Transfer objects to S3 Glacier Deep Archive after 2 years.

Discussion 0
Question # 40

A company needs to build a data lake in AWS. The company must provide row-level data access and column-level data access to specific teams. The teams will access the data by using Amazon Athena, Amazon Redshift Spectrum, and Apache Hive from Amazon EMR.

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

Options:

A.  

Use Amazon S3 for data lake storage. Use S3 access policies to restrict data access by rows and columns. Provide data access through Amazon S3.

B.  

Use Amazon S3 for data lake storage. Use Apache Ranger through Amazon EMR to restrict data access by rows and columns. Provide data access by using Apache Pig.

C.  

Use Amazon Redshift for data lake storage. Use Redshift security policies to restrict data access by rows and columns. Provide data access by using Apache Spark and Amazon Athena federated queries.

D.  

Use Amazon S3 for data lake storage. Use AWS Lake Formation to restrict data access by rows and columns. Provide data access through AWS Lake Formation.

Discussion 0
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