Free Amazon AWS-DEA-C01 Exam Questions

Question 1

Files from multiple data sources arrive in an Amazon S3 bucket on a regular basis. A data engineer wants to ingest new files into Amazon Redshift in near real time when the new files arrive in the S3 bucket. Which solution will meet these requirements?

A : Use the query editor v2 to schedule a COPY command to load new files into Amazon Redshift.

B : Use the zero-ETL integration between Amazon Aurora and Amazon Redshift to load new files into Amazon Redshift.

C : Use AWS Glue job bookmarks to extract, transform, and load (ETL) load new files into Amazon Redshift.

D : Use S3 Event Notifications to invoke an AWS Lambda function that loads new files into Amazon Redshift.

Answer: D

Question 2

A Cloud Data Engineering Consultant has been tasked with organizing access control for a team of analysts using an Amazon Redshift data warehouse. The team requires varying levels of access to sensitive financial data for reporting and analysis. The consultants need to define a strategy that provides the necessary access for the analysts to perform their duties while ensuring that principles of least privilege and data governance are upheld.

Which of the following actions should the consultant take to appropriately manage user access and permissions within the Amazon Redshift database? (Select TWO)

A : Implement row-level security within Redshift tables to control access to rows of data based on user roles, ensuring analysts only see data relevant to their analysis.

B : Grant superuser privileges to all analysts to ensure they have the ability to query all necessary tables within the Redshift cluster, then audit queries periodically for compliance.

C : Enable Amazon Redshift Spectrum to manage external tables and use IAM policies to grant access to these tables.

D : Set up database groups within Redshift and assign users to groups based on their access requirements, then grant group-specific permissions to the relevant schemas and tables.

E : Create individual IAM users for each analyst with attached policies that define the level of access to Redshift resources, and use those IAM users for database authentication.

Answer: A,D

Question 3

The Cloud Data Engineering team at an e-commerce company is tasked with analyzing historical sales data stored in CSV files in Amazon S3. They require a solution that allows them to directly query this data for their daily sales report, which will include product names, quantities sold, and total sales amounts. The solution should enable them to perform this task without the overhead of cluster management or data loading processes.

Which two steps are essential to set up this process (Select TWO)

A : Create an Amazon Redshift Spectrum external schema for the CSV files and run the query from an Amazon Redshift cluster.

B : Implement an AWS Lambda function to convert the CSV files into JSON format, as Athena cannot query CSV files directly.

C : Use AWS Data Pipeline to transfer the CSV files into an Amazon RDS instance and then query the data with Athena.

D : Write an Amazon Athena SQL query to select the necessary fields, aggregate the quantity and sales amount, and group the results by product name.

E : Use the AWS Glue Data Catalog to catalog the CSV files and define a schema that maps to the fields in the sales data.

Answer: D,E

Question 4

Files from multiple data sources arrive in an Amazon S3 bucket on a regular basis. A data engineer wants to ingest new files into Amazon Redshift in near real time when the new files arrive in the S3 bucket. Which solution will meet these requirements?

A : Use the query editor v2 to schedule a COPY command to load new files into Amazon Redshift.

B : Use the zero-ETL integration between Amazon Aurora and Amazon Redshift to load new files into Amazon Redshift.

C : Use AWS Glue job bookmarks to extract, transform, and load (ETL) load new files into Amazon Redshift.

D : Use S3 Event Notifications to invoke an AWS Lambda function that loads new files into Amazon Redshift.

Answer: D

Question 5

As a Data Engineer, you are tasked with setting up a batch data ingestion pipeline for a substantial financial dataset. This data is currently housed in an Amazon RDS database, stemming from various financial services and trading platforms. The dataset is complex and heterogeneous, predominantly in JSON format, and is updated nightly, typically ranging between 100-200 GB.

Your primary objective is to efficiently transfer this data from the RDS database to a data lake in AWS, ensuring reliable storage and preparing the dataset for analytical processing with minimal yet capable transformation steps due to its complexity.

Which combination of AWS services would be most appropriate?

A : Amazon AppFlow to facilitate the data transfer from Amazon RDS to Amazon S3. Afterward, utilize AWS Glue ETL for the data transformation processes.

B : Use AWS Database Migration Service (AWS DMS) to continuously replicate data from the Amazon RDS database to Amazon S3. Then, employ AWS Lambda for performing the necessary data transformations.

C : Configure AWS DataSync to transfer the JSON data nightly from the RDS database to Amazon S3. Subsequently, use AWS Glue ETL service to perform the necessary data transformations.

D : Use AWS Database Migration Service (AWS DMS) to continuously replicate data to Amazon S3. Configure an AWS Glue Crawler to update the schema in the Glue Data Catalog, and use Amazon Glue ETL for transformation jobs.

Answer: D