Question 1

A Cloud Data Engineer is tasked with setting up a secure and reliable connection from an AWS-based analytics service to an on-premises Microsoft SQL Server database. The goal is to perform regular data import operations.

Which approach would be most effective and secure for accomplishing this task?

Options :

A : Configure an AWS Lambda function within the VPC to use a JDBC connection with the database credentials hard-coded for simplicity and speed.

B : Implement an AWS Direct Connect link between the on-premises network and AWS, and use a JDBC connection with database credentials stored in Amazon RDS.

C : Use AWS DataSync with an ODBC connection to the SQL Server, ensuring the connection over the internet is encrypted with TLS.

D : Establish a VPN connection between the on-premises network and AWS VPC, and then use JDBC with SSL encryption to connect to the SQL Server.

Answer: D

Question 2

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?

Options :

A :

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.

B :

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.

C :

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.

D :

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.

Answer: C

Question 3

A Data Engineering Team needs to help the security team to deliver logs from various AWS services in their production AWS account to a centralized logging AWS account for security analysis. They plan to use Amazon Kinesis Data Streams for real-time log processing and delivery.

To ensure secure and efficient log delivery between accounts, where should the Kinesis Data Stream be deployed and what security considerations should be taken into account?

Options :

A : Set up the Kinesis Data Stream in the production account and configure it to push logs directly to the centralized logging account.

B : Implement the Kinesis Data Stream in the production account and use AWS Lambda for cross-account delivery of logs to the centralized logging account.

C : Deploy the Kinesis Data Stream in the centralized logging account and establish cross-account access for the production account to write logs to the stream.

D : Deploy Kinesis Data Streams in both accounts, using one for collecting logs and the other for receiving and processing these logs.

Answer: C

Question 4

A Cloud Data Engineering Team is overseeing a data lake stored in Amazon S3, which is experiencing evolving characteristics such as changes in data volume, schema, and frequency of access. To ensure the system remains robust and cost-effective, the team needs to implement solutions that manage these changes without significant disruption.

Which of the following strategies would effectively allow the team to handle the changing characteristics of the S3-stored data? (Select TWO)

Options :

A : Implement Amazon Glue Schema Registry to manage schema evolution and enforce schema compatibility across different data streams.

B : Configure AWS Lake Formation to centrally manage data security, lifecycle, and metadata, accommodating changes in data types and usage patterns.

C : Apply Amazon Redshift-s elastic resize feature to scale computing resources on-demand, anticipating fluctuations in data query volumes.

D : Maintain a static database schema within AWS Glue Data Catalog, ensuring that access to data remains consistent despite changes.

E : Employ Amazon S3 lifecycle policies to automatically transition data to the most appropriate storage class as access patterns change over time.

Answer: A,E

Question 5

A Cloud Data Engineering Team is implementing a system for real-time data ingestion through an API. The architecture needs to include data transformation before storage. The system must handle large files and store them efficiently post-transformation. The team is focused on using a serverless architecture on AWS, with an emphasis on Infrastructure as Code (IaC) for standardized and repeatable deployments across various environments.

Which combination of actions should the Cloud Data Engineering Team take to implement IaC for serverless deployments of data ingestion and transformation pipelines? (Select THREE)

Options :

A : Set up AWS Data Pipeline in the AWS SAM template for data movement and transformation.

B : Use AWS Elastic MapReduce (EMR) for data transformation in Kinesis Firehose.

C : Define an Amazon API Gateway in the AWS SAM template for data ingestion.

D : Configure DynamoDB in the AWS SAM template for storing the transformed data.

E : Utilize AWS Serverless Application Model (SAM) to declare AWS Lambda functions integrated with Amazon Kinesis Data Firehose.

F : Configure Amazon S3 bucket creation in the AWS SAM template for storing the transformed data.

Answer: C,E,F

Free AWS-DEA-C01 Mock Exam – Practice Online Confidently

Buying Options: