100% Free Amazon Data-Engineer-Associate Practice Test Questions

Question 1

As a Cloud Data Engineer, you have been tasked with optimizing an AWS Glue job that processes large datasets using Apache Spark. The job currently uses standard Spark DataFrames, but you are considering switching to AWS Glue DynamicFrames for better handling of schema variations and errors in the data.

Which of the following benefits is a primary advantage of using Glue DynamicFrames over standard Spark DataFrames in this scenario?

A : Glue DynamicFrames inherently support auto-scaling of Glue DPUs (Data Processing Units) based on the workload, thereby enhancing the performance of data processing tasks.

B : DynamicFrames provide enhanced support for handling semi-structured data and schema variations without requiring explicit schema definition, reducing the need for schema management in ETL processes.

C : The performance lag could be due to insufficient memory allocation for the Glue Data Processing Units (DPUs), which hinders Spark's in-memory data processing capabilities.

D : It's possible that the AWS Glue job is not leveraging Spark's advanced machine learning libraries, resulting in less efficient data processing compared to jobs that do use these libraries.

Answer: B

Question 2

A Cloud Data Engineering Consultant is tasked with setting up a secure data lake for a financial institution using AWS Lake Formation. The institution requires strict management of permissions to ensure that analysts have access only to the specific data necessary for their analysis tasks and are restricted from accessing sensitive customer financial records. The consultant must configure Lake Formation in such a way that permissions are granularly managed while facilitating the ease of access for authorized users.

Which of the following actions should the consultant take to correctly manage permissions through Lake Formation for the given requirements? (Select TWO)

A : Grant column-level permissions to the analysts' IAM roles for non-sensitive data tables within Lake Formation, ensuring precise access to data necessary for their tasks.

B : Apply tag-based access control in Lake Formation, tagging sensitive data and assigning corresponding permission tags to analysts' IAM roles for fine-grained access.

C : Set up database-level permissions for all analysts, granting SELECT privileges to ensure that analysts have broad access for exploratory analysis within the Lake Formation.

D : Implement row-level security by creating Lake Formation access control lists that map to analysts' roles, permitting them to query only the rows pertinent to their analysis.

E : Configure Lake Formation to use named resource links for sensitive tables, providing analysts with indirect access to data through a resource link that obscures the underlying data source.

Answer: A,B

Question 3

A company stores its processed data in an S3 bucket. The company has a strict data access policy. Thecompany uses IAM roles to grant teams within the company different levels of access to the S3 bucket.The company wants to receive notifications when a user violates the data access policy. Each notificationmust include the username of the user who violated the policy.Which solution will meet these requirements?

A : Use AWS Config rules to detect violations of the data access policy. Set up compliance alarms.

B : Use Amazon CloudWatch metrics to gather object-level metrics. Set up CloudWatch alarms.

C : Use AWS CloudTrail to track object-level events for the S3 bucket. Forward events to Amazon CloudWatch to set up CloudWatch alarms.

D : Use Amazon S3 server access logs to monitor access to the bucket. Forward the access logs to an Amazon CloudWatch log group. Use metric filters on the log group to set up CloudWatch alarms.

Answer: C

Question 4

A medium-sized enterprise with fluctuating data analytics demands is exploring Amazon Redshift options. They are looking for a configuration that minimizes the need for active resource management, especially during unpredictable periods of high query volume. The ideal solution should adapt to changing demands while maintaining operational efficiency.

Which Redshift configuration should they consider to meet these requirements of adaptability and ease of management?

A : Choose Redshift Serverless, as it provides the flexibility to automatically adapt to changing query volumes without manual scaling.

B : Opt for Redshift with RA3 nodes, which offer scalable storage and compute capabilities, and configure auto-scaling policies to handle variable query loads.

C : Select Redshift with On-Demand pricing and set up scaling triggers based on performance metrics to manage varying loads efficiently.

D : Implement a traditional Redshift cluster with dense compute nodes, using dynamic resizing features for adapting to fluctuating workloads.

Answer: A

Question 5

A telecommunications company collects network usage data throughout each day at a rate of several thousanddata points each second. The company runs an application to process the usage data in real time. Thecompany aggregates and stores the data in an Amazon Aurora DB instance.Sudden drops in network usage usually indicate a network outage. The company must be able to identifysudden drops in network usage so the company can take immediate remedial actions.Which solution will meet this requirement with the LEAST latency?

A : Create an AWS Lambda function to query Aurora for drops in network usage. Use Amazon EventBridge to automatically invoke the Lambda function every minute.

B : Modify the processing application to publish the data to an Amazon Kinesis data stream. Create an Amazon Managed Service for Apache Flink (previously known as Amazon Kinesis Data Analytics) application to detect drops in network usage.

C : Replace the Aurora database with an Amazon DynamoDB table. Create an AWS Lambda function to query the DynamoDB table for drops in network usage every minute. Use DynamoDB Accelerator (DAX) between the processing application and DynamoDB table.

D : Create an AWS Lambda function within the Database Activity Streams feature of Aurora to detect drops in network usage.

Answer: B

Free Practice Amazon Data-Engineer-Associate Exam Questions 2025