Data-Engineer-Associate Exam Dumps - AWS Certified Data Engineer - Associate (DEA-C01)

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Question # 4

A company has as JSON file that contains personally identifiable information (PIT) data and non-PII data. The company needs to make the data available for querying and analysis. The non-PII data must be available to everyone in the company. The PII data must be available only to a limited group of employees. Which solution will meet these requirements with the LEAST operational overhead?

Store the JSON file in an Amazon S3 bucket. Configure AWS Glue to split the file into one file that contains the PII data and one file that contains the non-PII data. Store the output files in separate S3 buckets. Grant the required access to the buckets based on the type of user.

Store the JSON file in an Amazon S3 bucket. Use Amazon Macie to identify PII data and to grant access based on the type of user.

Store the JSON file in an Amazon S3 bucket. Catalog the file schema in AWS Lake Formation. Use Lake Formation permissions to provide access to the required data based on the type of user.

Create two Amazon RDS PostgreSQL databases. Load the PII data and the non-PII data into the separate databases. Grant access to the databases based on the type of user.

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Question # 5

A company is building a data lake for a new analytics team. The company is using Amazon S3 for storage and Amazon Athena for query analysis. All data that is in Amazon S3 is in Apache Parquet format.

The company is running a new Oracle database as a source system in the company's data center. The company has 70 tables in the Oracle database. All the tables have primary keys. Data can occasionally change in the source system. The company wants to ingest the tables every day into the data lake.

Which solution will meet this requirement with the LEAST effort?

Create an Apache Sqoop job in Amazon EMR to read the data from the Oracle database. Configure the Sqoop job to write the data to Amazon S3 in Parquet format.

Create an AWS Glue connection to the Oracle database. Create an AWS Glue bookmark job to ingest the data incrementally and to write the data to Amazon S3 in Parquet format.

Create an AWS Database Migration Service (AWS DMS) task for ongoing replication. Set the Oracle database as the source. Set Amazon S3 as the target. Configure the task to write the data in Parquet format.

Create an Oracle database in Amazon RDS. Use AWS Database Migration Service (AWS DMS) to migrate the on-premises Oracle database to Amazon RDS. Configure triggers on the tables to invoke AWS Lambda functions to write changed records to Amazon S3 in Parquet format.

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Question # 6

A data engineer is troubleshooting an AWS Glue workflow that occasionally fails. The engineer determines that the failures are a result of data quality issues. A business reporting team needs to receive an email notification any time the workflow fails in the future.

Which solution will meet this requirement?

Create an Amazon Simple Notification Service (Amazon SNS) FIFO topic. Subscribe the team's email account to the SNS topic. Create an AWS Lambda function that initiates when the AWS Glue job state changes to FAILED. Set the SNS topic as the target.

Create an Amazon Simple Notification Service (Amazon SNS) standard topic. Subscribe the team's email account to the SNS topic. Create an Amazon EventBridge rule that triggers when the AWS Glue Job state changes to FAILED. Set the SNS topic as the target.

Create an Amazon Simple Queue Service (Amazon SQS) FIFO queue. Subscribe the team's email account to the SQS queue. Create an AWS Config rule that triggers when the AWS Glue job state changes to FAILED. Set the SQS queue as the target.

Create an Amazon Simple Queue Service (Amazon SQS) standard queue. Subscribe the team's email account to the SQS queue. Create an Amazon EventBridge rule that triggers when the AWS Glue job state changes to FAILED. Set the SQS queue as the target.

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Question # 7

A company loads transaction data for each day into Amazon Redshift tables at the end of each day. The company wants to have the ability to track which tables have been loaded and which tables still need to be loaded.

A data engineer wants to store the load statuses of Redshift tables in an Amazon DynamoDB table. The data engineer creates an AWS Lambda function to publish the details of the load statuses to DynamoDB.

How should the data engineer invoke the Lambda function to write load statuses to the DynamoDB table?

Use a second Lambda function to invoke the first Lambda function based on Amazon CloudWatch events.

Use the Amazon Redshift Data API to publish an event to Amazon EventBridqe. Configure an EventBridge rule to invoke the Lambda function.

Use the Amazon Redshift Data API to publish a message to an Amazon Simple Queue Service (Amazon SQS) queue. Configure the SQS queue to invoke the Lambda function.

Use a second Lambda function to invoke the first Lambda function based on AWS CloudTrail events.

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Question # 8

During a security review, a company identified a vulnerability in an AWS Glue job. The company discovered that credentials to access an Amazon Redshift cluster were hard coded in the job script.

A data engineer must remediate the security vulnerability in the AWS Glue job. The solution must securely store the credentials.

Which combination of steps should the data engineer take to meet these requirements? (Choose two.)

Store the credentials in the AWS Glue job parameters.

Store the credentials in a configuration file that is in an Amazon S3 bucket.

Access the credentials from a configuration file that is in an Amazon S3 bucket by using the AWS Glue job.

Store the credentials in AWS Secrets Manager.

Grant the AWS Glue job 1AM role access to the stored credentials.

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Answer:

Explanation:

AWS Secrets Manager is a service that allows you to securely store and manage secrets, such as database credentials, API keys, passwords, etc. You can use Secrets Manager to encrypt, rotate, and audit your secrets, as well as to control access to them using fine-grained policies. AWS Glue is a fully managed service that provides a serverless data integration platform for data preparation, data cataloging, and data loading. AWS Glue jobs allow you to transform and load data from various sources into various targets, using either a graphical interface (AWS Glue Studio) or a code-based interface (AWS Glue console or AWS Glue API).

Storing the credentials in AWS Secrets Manager and granting the AWS Glue job 1AM role access to the stored credentials will meet the requirements, as it will remediate the security vulnerability in the AWS Glue job and securely store the credentials. By using AWS Secrets Manager, you can avoid hard coding the credentials in the job script, which is a bad practice that exposes the credentials to unauthorized access or leakage. Instead, you can store the credentials as a secret in Secrets Manager and reference the secret name or ARN in the job script. You can also use Secrets Manager to encrypt the credentials using AWS Key Management Service (AWS KMS), rotate the credentials automatically or on demand, and monitor the access to the credentials using AWS CloudTrail. By granting the AWS Glue job 1AM role access to the stored credentials, you can use the principle of least privilege to ensure that only the AWS Glue job can retrieve the credentials from Secrets Manager. You can also use resource-based or tag-based policies to further restrict the access to the credentials.

The other options are not as secure as storing the credentials in AWS Secrets Manager and granting the AWS Glue job 1AM role access to the stored credentials. Storing the credentials in the AWS Glue job parameters will not remediate the security vulnerability, as the job parameters are still visible in the AWS Glue console and API. Storing the credentials in a configuration file that is in an Amazon S3 bucket and accessing the credentials from the configuration file by using the AWS Glue job will not be as secure as using Secrets Manager, as the configuration file may not be encrypted or rotated, and the access to the file may not be audited or controlled.Â References:

AWS Secrets Manager

AWS Glue

AWS Certified Data Engineer - Associate DEA-C01 Complete Study Guide, Chapter 6: Data Integration and Transformation, Section 6.1: AWS Glue

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