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Data Engineer DEA-C01 Practice Questions

Certified Data Engineer Associate

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Question 1

A company uses an Amazon Redshift cluster that runs on RA3 nodes. The company wants to scale read and write capacity to meet demand. A data engineer needs to identify a solution that will turn on concurrency scaling.

Which solution will meet this requirement?

Turn on concurrency scaling in workload management (WLM) for Redshift Serverless workgroups.
Turn on concurrency scaling at the workload management (WLM) queue level in the Redshift cluster.
Turn on concurrency scaling in the settings during the creation of any new Redshift cluster.
Turn on concurrency scaling for the daily usage quota for the Redshift cluster.

Select an answer above, then submit your vote. Reading or practicing does not cast a vote.

Question 2

A data engineer manages an Amazon S3 Standard bucket that stores a large dataset. Multiple applications and users need to access separate parts of the dataset. The data engineer must establish granular access control.

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

Use IAM roles to assign permissions to individual users.
Use Amazon S3 access points to manage access.
Create a separate S3 bucket for each application and user.
Implement S3 bucket policies to manage access.

Select an answer above, then submit your vote. Reading or practicing does not cast a vote.

Question 3

A data engineer needs to maintain a central metadata repository that users access through Amazon EMR and Amazon Athena queries. The repository needs to provide the schema and properties of many tables. Some of the metadata is stored in Apache Hive. The data engineer needs to import the metadata from Hive into the central metadata repository.

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

Use Amazon EMR and Apache Ranger.
Use a Hive metastore on an EMR cluster.
Use the AWS Glue Data Catalog.
Use a metastore on an Amazon RDS for MySQL DB instance.

Select an answer above, then submit your vote. Reading or practicing does not cast a vote.

Question 4

A data engineer needs to configure an AWS Glue connection to access a PostgreSQL database. The database is running on an Amazon EC2 instance in a private subnet. The database requires secure credential management. Additionally, the connection must use SSL. The data engineer needs to create the connection that an AWS Glue crawler will use to catalog the database.

Which solution will meet these requirements?

Create a Java Database Connectivity (JDBC) connection that uses a PostgreSQL JDBC URL. Enter the username and password in the connection properties. Select a VPC, subnet, and security group. Enable the Skip certificate validation option.
Create a Java Database Connectivity (JDBC) connection that uses a PostgreSQL JDBC URL. Store the credentials in AWS Secrets Manager. Select a VPC, subnet, and security group. Choose the Require SSL connection option.
Create a network connection type that uses a PostgreSQL endpoint URL. Store the credentials in AWS Secrets Manager. Select a VPC and security group. Choose the Require SSL connection option.
Create a network connection type that uses a PostgreSQL Java Database Connectivity (JDBC) URL. Enter the username and password in the connection properties. Select a VPC and subnet. Upload a custom JDBC driver to an Amazon S3 bucket.

Select an answer above, then submit your vote. Reading or practicing does not cast a vote.

Question 5

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?

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.
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.
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.
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.

Select an answer above, then submit your vote. Reading or practicing does not cast a vote.

Question 6

A company uses an Amazon S3 bucket to integrate multiple data sources into a central data lake. The company needs to perform multiple transformations and data cleaning processes on the data to make the data accessible to business partners.

The company needs a solution that will give multiple business partners the ability to run SQL queries on the central data lake during normal business hours.

Which solution will meet these requirements MOST cost-effectively?

Use a provisioned Amazon EMR cluster after normal business hours to process the previous day's data, apply all necessary transformations, and load the prepared data into Amazon Redshift Serverless.
Use an AWS Glue Flex job after normal business hours to process the previous day's data, apply all necessary transformations, and load the prepared data into Amazon Redshift Serverless.
Use an AWS Lambda function after normal business hours to process the previous day's data, apply all necessary transformations, and load the prepared data into an Amazon Redshift provisioned cluster.
Use an AWS Glue Flex job after normal business hours to process the previous day's data, apply all necessary transformations, and load the prepared data into an Amazon Redshift provisioned cluster.

Select an answer above, then submit your vote. Reading or practicing does not cast a vote.

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