【評判】Practice Exams | AWS Certified Data Engineer Associate[2025]

Ace your AWS Certified Data Engineer Associate DAE-C01 exam!
Get used to the exam conditions by equal requirements in the practice exams!
Learn through the detailed explanations for each question - including references!
Develop the ability to quickly think your way into new scenarios that you will need in the real exam!
Study for all topic areas specified in the official exam guide!

Gain an edge in the AWS Certified Data Engineer Associate (DEA-C01) certification with this pioneering practice exam course. The course presents 215 scenario-based questions across six unique practice exams.

Reflecting the exam's four domains and culminating in a comprehensive final test that simulates the real-world exam experience, this course offers an unmatched preparation advantage. Every answer comes with an in-depth explanation that not only highlights the correct choices but also deepens your grasp of the material for thorough mastery.

Constructed to align with the official exam guide and AWS's sample questions, the practice exams ensure relevant and current preparation. Learners will explore detailed explanations for each option, comprehending the correct answers and the reasons why other options fall short. This method, bolstered by direct AWS documentation references, provides a profound and durable understanding of the subject matter.

As the first comprehensive practice suite for the DEA-C01 certification, this course is designed to close the gap between knowledge and application. It's crafted to empower you to approach the certification with confidence and secure a credential that opens new professional doors.

Get ready to push your limits, upgrade your skills, and position yourself at the vanguard of AWS Data Engineering experts with this leading practice exam course.

SAMPLE QUESTION

A Cloud Data Engineering Consultant has been tasked with optimizing the data transfer process between Amazon S3 and Amazon Redshift for a client. The client's data warehousing solution requires regular loading of large datasets into Redshift for complex querying, as well as periodic unloading of query results back into S3 for long-term storage and further processing. The consultant needs to ensure that these load and unload operations are performed efficiently and securely.

Which combination of methods should the consultant recommend to perform these operations effectively? (Select TWO)

A) Utilize the COPY command in Amazon Redshift to parallelize data loads from Amazon S3, making use of Redshift's MPP (Massively Parallel Processing) architecture.

B) Use the INSERT INTO command to load data from S3 to Amazon Redshift, ensuring transactions are logged for data integrity.

C) Implement Redshift Spectrum to directly query data on Amazon S3 without loading it into Redshift, reducing data movement.

D) Configure Redshift to automatically unload query results to S3 using the UNLOAD command, with encryption enabled for data security.

E) Set up AWS Data Pipeline with a custom script for moving data between S3 and Redshift, allowing for complex data transformation during the transfer.

Now take a guess. The correct answer is... [SCROLL DOWN]

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

.

Correct Answers:

Utilize the COPY command in Amazon Redshift to parallelize data loads from Amazon S3, making use of Redshift's MPP (Massively Parallel Processing) architecture.

• The COPY command is specifically designed for bulk data loading into Amazon Redshift from Amazon S3. It takes advantage of Redshift's MPP architecture to execute fast parallel loads, which is ideal for handling large datasets efficiently.

Configure Redshift to automatically unload query results to S3 using the UNLOAD command, with encryption enabled for data security.

• The UNLOAD command in Amazon Redshift is designed to export data to S3. It can perform parallel unloads, similar to the COPY command, and supports encryption to maintain data security during the transfer process.

Incorrect Answers:

Use the INSERT INTO command to load data from S3 to Amazon Redshift, ensuring transactions are logged for data integrity.

• The INSERT INTO command can be used for adding data into Amazon Redshift, but it is not suitable for bulk operations. It is less efficient than the COPY command for large datasets due to the way it handles individual transactions.

Implement Redshift Spectrum to directly query data on Amazon S3 without loading it into Redshift, reducing data movement.

• While Redshift Spectrum allows querying data in S3 without loading it into Redshift, this scenario specifically requires data movement for further processing, making Spectrum an auxiliary tool rather than a primary method for load/unload operations.

Set up AWS Data Pipeline with a custom script for moving data between S3 and Redshift, allowing for complex data transformation during the transfer.

• AWS Data Pipeline is a service for orchestrating data movement, but for the specific use case of moving data between S3 and Redshift, using the native COPY and UNLOAD commands is more efficient and less complex than writing custom scripts in Data Pipeline.

Reference:

• Loading Data from Amazon S3

• Unloading Data to Amazon S3

Note: There will be links in the actual practice exams in the reference section.