AWS Data Engineer Associate - Test 11

The AWS data engineer certification DEA-C01 mock test is a validation tool for your AWS knowledge. It helps you prepare for certification and demonstrates initiative. However, certifications alone don’t make you job-ready. Employers expect candidates to master Tableau, SQL, SAS, and Azure, while also gaining data engineering expertise in Snowflake, Databricks, and PySpark. Data science and AI skills in TensorFlow, PyTorch, LLMs, and Generative AI are equally critical.

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Welcome to your AWS Data Engineer Associate – Test-11

Name

Phone

Q1. A media company wants to process and analyze historical viewership data that is periodically dumped into Amazon S3. The data needs to be transformed and loaded into an Amazon Redshift cluster for analysis. Which AWS service should they use for efficient processing and loading of this batch data?

Select 1 option(s):

AWS Database Migration Service (AWS DMS)

Amazon EMR

Amazon AppFlow

AWS Lambda

Q2. A retail company wants to process and analyze streaming data from point-of-sale (POS) systems across various stores in real-time. Which AWS service is best suited for efficiently ingesting and processing this streaming data?

Select 1 option(s):

Amazon S3

Amazon RDS

Amazon Kinesis Data Streams

AWS Lambda

Q3. A company is building a data processing pipeline that involves running data transformation tasks at specific times of the day. They want a service that can automate the scheduling and execution of these tasks and provide monitoring and logging capabilities. Which AWS service can meet these requirements?

Select 1 option(s):

Amazon EC2 (Elastic Compute Cloud)

AWS Glue

Amazon MWAA (Managed Apache Airflow)

Amazon Kinesis

Q4. A retail company wants to analyze customer purchase behavior by processing transaction data in real-time. The solution should be capable of handling continuous data streams and provide timely insights. Which AWS service is the best choice for this requirement?

Select 1 option(s):

Amazon DynamoDB

Amazon EC2

Amazon Kinesis Data Streams

Amazon S3

Q5. An e-commerce company needs to regularly ingest and transform large volumes of sales data stored in Amazon S3 into a format suitable for analysis. The ingestion process should be automated and occur daily. Which AWS service is best suited for this batch data ingestion and transformation task?

Select 1 option(s):

AWS Lambda

Amazon Redshift

AWS Glue

Amazon AppFlow

Q6. A media company needs to analyze web server logs stored in CSV format. The analysis involves complex queries and joins. The data is not frequently accessed but needs to be available for ad-hoc queries. Which combination of AWS services is most appropriate for this use case?

Select 1 option(s):

Amazon S3 and Amazon Athena

Amazon DynamoDB and Amazon Redshift

Amazon EBS and Amazon RDS

Amazon EC2 and Amazon EFS

Q7. Your team is building a real-time analytics system that requires low-latency data ingestion. Which AWS service is most suitable for this requirement, particularly considering throughput and latency characteristics?

Select 1 option(s):

AWS Glue

Amazon Kinesis Data Streams

Amazon S3

Amazon RDS

Q8. A company is migrating its on-premises legacy database to AWS. The database primarily handles OLTP workloads and requires high availability and consistent performance. Which AWS service is the most suitable for this migration?

Select 1 option(s):

Amazon S3

Amazon DynamoDB

Amazon RDS

Amazon Glacier

Q9. An enterprise needs to aggregate, catalog, and securely store data coming from various sources such as IoT devices, social media, and transactional systems. The solution should facilitate data analysis and governance. Which AWS service would best meet these requirements?

Select 1 option(s):

Amazon EMR

Amazon S3

AWS Lake Formation

Amazon Kinesis

Q10. A company needs to ingest large volumes of data from various sources at high throughput. Which AWS service should they choose to meet these throughput and latency characteristics?

Select 1 option(s):

Amazon SQS

Amazon Redshift

Amazon Kinesis Data Firehose

AWS Lambda

Q11. A financial institution requires a data storage solution to perform real-time analytics on transactional data. The data needs to be frequently updated and queried. Which AWS service is most appropriate to meet these specific access patterns and performance requirements?

Select 1 option(s):

Amazon Redshift

Amazon RDS

Amazon DynamoDB

Amazon S3

Q12. Your company is setting up a data lake on AWS for storing large-scale analytics data. The data is in Apache Parquet format and will be used for complex ad-hoc queries. Which AWS service is the most suitable for this purpose?

Select 1 option(s):

Amazon RDS

Amazon DynamoDB

Amazon S3

Amazon EC2

Q13. A media streaming company is using Amazon S3 to store and distribute video content to users. They want to ensure that all data transferred from S3 to the users devices is encrypted during transit. Which AWS service or feature should they enable to achieve this goal effectively?

Select 1 option(s):

Use Amazon S3 server-side encryption with AWS KMS-managed keys.

Enable Amazon S3 transfer acceleration to encrypt data in transit.

Implement AWS CloudFront with HTTPS to distribute content securely.

Enable Amazon S3 bucket policies for encryption in transit.

Q14. A company is building a data processing pipeline that involves running multiple AWS Lambda functions in a specific sequence. They need a service that can orchestrate the execution of these Lambda functions, pass data between them, and handle errors gracefully. Which AWS service is suitable for this scenario?

Select 1 option(s):

Amazon S3

Amazon SQS (Simple Queue Service)

AWS Step Functions

Amazon Kinesis

Q15. A healthcare analytics company needs to ensure that their data ingestion pipeline can reprocess data in case of failures or updates in processing logic. Which AWS service would be most effective for enabling replayability of data in their ingestion pipeline?

Select 1 option(s):

Amazon S3

AWS Lambda

Amazon Kinesis Data Streams

Amazon RDS

Q16. A data engineer is designing an automated data processing pipeline that requires running containerized tasks without the need to manage the underlying infrastructure. They want to ensure scalability and flexibility in their solution. Which AWS service is suitable for this use case?

Select 1 option(s):

Amazon EC2 (Elastic Compute Cloud)

AWS Lambda

Amazon ECS (Elastic Container Service)

AWS Fargate

Q17. A data engineer is responsible for maintaining a data processing workflow that includes multiple AWS services. They want to automate error detection and notification in the workflow to ensure it runs smoothly. Which AWS service or feature should they use for this purpose?

Select 1 option(s):

AWS Lambda

Amazon S3 Event Notifications

AWS Step Functions

Amazon Simple Queue Service (SQS)

Q18. A company wants to automatically process new images uploaded to an Amazon S3 bucket and generate thumbnails. Which service should be used to trigger a thumbnail generation function each time a new image is uploaded to the bucket?

Select 1 option(s):

AWS Lambda

Amazon EC2

Amazon S3 Event Notifications

Amazon Kinesis Data Streams

Q19. In an application deployed on AWS, sensitive data is being stored in an Amazon DynamoDB table. To enhance data security, the team decides to implement key salting techniques. Which of the following methods should they adopt for effective key salting in this scenario?

Select 1 option(s):

Use DynamoDB‘s built-in salting feature for sensitive data items.

Apply AWS Lambda functions to automatically add a salt to sensitive data before storing it in DynamoDB.

Enable DynamoDB encryption at rest with salted key encryption.

Configure AWS WAF to add salt to sensitive data before it is stored in DynamoDB.

Q20. Your organization needs to store a large volume of sensor data collected from IoT devices. The data will be ingested continuously and needs to be available for frequent access and analysis. Which AWS storage service would be most appropriate?

Select 1 option(s):

Amazon DynamoDB

Amazon EBS

Amazon Glacier

Amazon Redshift

Q21. In an Amazon Redshift environment, a team needs to perform maintenance tasks without risking data integrity due to concurrent write operations. What should they implement to prevent write access to specific tables during maintenance?

Select 1 option(s):

Enable Redshift‘s Concurrency Scaling.

Use Redshift‘s Table-Level Restore.

Implement Redshift‘s Automatic WLM

Apply Redshift‘s Manual Table Locks.

Q22. A data engineer is building a data processing application that needs to interact with various AWS services, including Amazon DynamoDB and Amazon S3. The engineer wants to use a programming language of their choice and needs to call SDKs to access AWS features from the code. Which AWS service allows the engineer to achieve this flexibility?

Select 1 option(s):

AWS Glue

AWS Lambda

Amazon Kinesis

AWS SDK for JavaScript (AWS Amplify)

Q23. A financial institution is planning to ingest high-frequency trading data into its AWS environment. The data needs to be processed immediately upon arrival. Which EC2 instance type would be most appropriate for this use case, considering the need for high compute power and low-latency network performance?

Select 1 option(s):

t2.micro

c5n.18xlarge

m5.large

r5.xlarge

Q24. A data engineer is building a data processing pipeline using AWS services. They need to ensure that API calls for data processing tasks are monitored, logged, and can be audited for security and compliance purposes. Which AWS service should they use for this requirement?

Select 1 option(s):

AWS CloudTrail

Amazon Kinesis

AWS Step Functions

Amazon S3

Q25. A data engineering team is designing a data transfer solution to AWS. They need to decide between client-side encryption and server-side encryption for transferring sensitive data. Which of the following statements accurately describes a key difference between these two encryption methods that should be considered?

Select 1 option(s):

Client-side encryption allows AWS to manage the encryption keys, whereas server-side encryption requires the customer to manage the keys.

Reduced capServer-side encryption encrypts data before it is transmitted over the network, while client-side encryption does not.ital expenditure

Client-side encryption encrypts the data before it leaves the customer‘s environment, whereas server-side encryption encrypts the data after it arrives at AWS.

Server-side encryption offers higher performance than client-side encryption.

Q26. An organizations data processing pipeline involves multiple AWS services and data sources. The data engineer in charge needs to troubleshoot performance issues in the pipeline and identify bottlenecks. Which AWS service can help them collect performance metrics and analyze the data processing workflow?

Select 1 option(s):

AWS Data Pipeline

AWS CloudTrail

AWS X-Ray

AWS Glue

Q27. A data engineer is building an automated ETL (Extract, Transform, Load) pipeline that needs to execute code in response to changes in Amazon S3 buckets. They want to ensure that the code runs without provisioning or managing servers. Which AWS service can meet this requirement?

Select 1 option(s):

Amazon EC2 (Elastic Compute Cloud)

AWS Lambda

Amazon ECS (Elastic Container Service)

AWS Fargate

Q28. An online retail company is using a stream processing solution for real-time analytics of customer purchase data. They need to ensure that the data can be re-ingested from the same point in the stream in case of processing failures. Which feature should they implement in their AWS environment to enable this?

Select 1 option(s):

AWS Glue Job Bookmark

Kinesis Data Streams Shard Iterator

Amazon SQS Message Retention

Amazon S3 Versioning

Q29. An organization uses AWS Glue for data processing and needs to ensure that their script logs, stored in Amazon CloudWatch, are encrypted. What is the most effective method to achieve this?

Select 1 option(s):

Enable AWS Glue job bookmarks to encrypt CloudWatch logs.

Utilize AWS CloudWatch Logs encryption with AWS KMS-managed keys.

Implement VPC endpoint policies for AWS Glue to encrypt logs.

Use AWS Glue data encryption settings to encrypt CloudWatch logs.

Q30. A data engineer needs to ingest data from a third-party service that exposes a REST API, updating every 30 minutes. The data needs to be stored in AWS for analysis. Which AWS service should be used to consume the data API and ingest the data efficiently?

Select 1 option(s):

AWS Lambda

Amazon Kinesis Data Firehose

Amazon EC2

Amazon RDS

Q31. A data engineering team is implementing a password storage system on AWS. They want to enhance the security of the stored passwords by using key salting techniques. Which of the following approaches should they use to incorporate key salting effectively?

Select 1 option(s):

Utilize AWS KMS to automatically append a unique salt value to each password before encryption.

Implement a custom solution where a unique salt is generated and appended to each password before hashing.

Enable AWS RDS encryption with salted password encryption.

Use AWS Secrets Manager to store pre-salted passwords.

Q32. A company is planning to deploy a data storage solution on AWS and is considering between Amazon S3 (a managed service) and setting up a file storage system on Amazon EC2 instances (an unmanaged service). What is a key difference in terms of authentication mechanisms between these two options?

Select 1 option(s):

Amazon S3 inherently supports AWS IAM for access control, while EC2-based file storage would require manual setup of IAM roles and policies.

EC2-based file storage inherently supports multi-factor authentication (MFA), while Amazon S3 does not.

Amazon S3 requires an external identity provider for authentication, whereas EC2-based file storage does not.

EC2-based file storage can only use network-based authentication, unlike Amazon S3 which uses API-based authentication.

Q33. A data engineer is setting up a batch ingestion pipeline to transfer large datasets from an on-premises database to Amazon Redshift nightly. Which configuration option would optimize the data transfer performance?

Select 1 option(s):

Enable Multi-AZ deployments on Amazon Redshift.

Use AWS Database Migration Service (AWS DMS) with change data capture (CDC).

Implement Amazon Redshift Spectrum for direct querying.

Configure Amazon Redshift to use dense compute (DC2) nodes.

Q34. A data engineer is tasked with processing large volumes of log data stored in Amazon S3. The engineer needs to perform distributed data processing and analysis using a managed service. Which AWS service should the engineer choose to efficiently process this data?

Select 1 option(s):

Amazon Redshift

Amazon RDS

Amazon EMR

AWS Lambda

Q35. An application logs user activity data to an Amazon S3 bucket. A data engineer needs to set up a system to analyze these logs in near-real-time. Which AWS service should be used to trigger the analysis process each time a new log file is written to the S3 bucket?

Select 1 option(s):

Amazon EC2 Auto Scaling

Amazon S3 Event Notifications

AWS Data Pipeline

Amazon RDS

Q36. A research team needs to store a vast amount of environmental data collected from sensors. The data is in plain text (.txt) format and will be used for occasional complex analytics. Which AWS service is the most appropriate for storing and processing this data?

Select 1 option(s):

Amazon RDS

Amazon Redshift

Amazon S3

Amazon DynamoDB

Q37. A data engineer is responsible for orchestrating complex data pipelines that involve multiple data processing tasks and dependencies. They need a service that can help them design, schedule, and monitor these pipelines efficiently. Which AWS service is designed for orchestrating data pipelines and providing Apache Airflow as a managed environment?

Select 1 option(s):

Amazon S3

AWS Lambda

Amazon MWAA (Managed Apache Airflow)

Amazon RDS (Relational Database Service)

Q38. Your organization requires a storage solution for a web application that will frequently read and occasionally update user profile data. The data must be accessible with low latency and the solution should be capable of handling sudden increases in traffic. Which AWS service is most appropriate for this scenario?

Select 1 option(s):

Amazon RDS

Amazon S3

Amazon DynamoDB

Amazon EFS

Q39. A data engineer is tasked with orchestrating a complex data pipeline that involves multiple AWS services and requires conditional logic and error handling. Which AWS service is designed for orchestrating data pipelines, allowing for conditional branching, retries, and handling various AWS services?

Select 1 option(s):

AWS Step Functions

Amazon S3

AWS Lambda

Amazon Redshift

Q40. A company is using AWS Glue for their ETL processes. They need to ensure that the data stored in the AWS Glue Data Catalog is encrypted. Which of the following options should be used to meet this requirement?

Select 1 option(s):

Enable server-side encryption with Amazon S3-managed keys (SSE-S3) for the AWS Glue Data Catalog.

Use AWS Key Management Service (KMS) customer-managed keys for the AWS Glue Data Catalog encryption.

Implement client-side encryption before storing metadata in the AWS Glue Data Catalog.

Apply AWS Glue security configurations to encrypt network traffic.

Q41. A company needs to store and regularly process log files generated by their application. The logs are in text format and the processing involves searching and filtering operations. Which combination of AWS services should be used to efficiently store and process this data?

Select 1 option(s):

Amazon S3 and AWS Lambda

Amazon EC2 and Amazon EBS

Amazon Glacier and Amazon Redshift

Amazon DynamoDB and AWS Glue

Q42. A data engineer is building a data processing pipeline that involves executing custom scripts for data cleansing and transformation. They want to ensure that these scripts are executed efficiently and can scale based on the workload. Which AWS service provides serverless compute capabilities and accepts custom scripts for data processing?

Select 1 option(s):

Amazon EC2 (Elastic Compute Cloud)

AWS Fargate

AWS Batch

AWS Lambda

Q43. A company needs to store relational data with high transaction rates and requires immediate consistency. The data will be used for online transaction processing (OLTP). Which AWS service should be used?

Select 1 option(s):

Amazon DynamoDB

Amazon RDS

Amazon S3

Amazon Redshift

Q44. Your company requires a storage solution for large-scale, unstructured data that can be accessed globally with low latency. The data is frequently accessed and requires high durability. Which AWS storage solution is most suitable?

Select 1 option(s):

Amazon S3

Amazon RDS

Amazon EBS

Amazon Redshift

Q45. An e-commerce platform needs to ingest user activity data from its website at the end of each day, process the data, and then load it into Amazon Redshift for analysis. Which AWS service combination is most appropriate for this batch data ingestion and processing?

Select 1 option(s):

AWS Glue and Amazon Redshift

Amazon EC2 and AWS Lambda

Amazon S3 and Amazon Kinesis Data Streams

AWS Data Pipeline and Amazon Redshift

Q46. A startup is developing a new online booking system that requires a database to handle frequent read and write operations with high availability and automated backups. The database should also allow for easy scaling as the user base grows. Which AWS service should be used for this scenario?

Select 1 option(s):

Amazon DynamoDB

Amazon RDS

Amazon Redshift

Amazon S3

Q47. A financial services company needs to ensure that personally identifiable information (PII) in their Amazon DynamoDB tables is masked when accessed by certain users. Which approach is most appropriate for masking this data in DynamoDB?

Select 1 option(s):

Apply server-side encryption in DynamoDB with AWS KMS.

Implement Amazon DynamoDB fine-grained access control rules.

Use AWS Glue DataBrew to mask PII data in DynamoDB.

Configure DynamoDB Streams to trigger AWS Lambda for data masking.

Q48. A data engineer wants to set up a complex workflow that involves triggering multiple AWS Glue crawlers and ETL jobs in a specific sequence. The workflow should run every week. Which tool is most suitable for orchestrating and scheduling this workflow?

Select 1 option(s):

AWS Lambda

Amazon EventBridge

Apache Airflow

Amazon S3

Q49. A data engineer is working on a project that requires running custom scripts for data processing. They need a service that accepts scripting for tasks like data transformation and analysis. Which AWS service should they choose for this purpose?

Select 1 option(s):

Amazon S3

AWS Glue

Amazon Redshift

AWS Lambda

Q50. A company is using Amazon RDS to store customer data. For compliance reasons, they need to mask credit card information in their database before providing access to their analytics team. Which AWS service or feature should they use to achieve this requirement effectively?

Select 1 option(s):

Enable Amazon RDS encryption at rest.

Utilize AWS Key Management Service (KMS) for data masking.

Implement AWS Lambda functions to mask data on retrieval.

Use Amazon RDS dynamic data masking features.

Q51. A company is streaming real-time data from IoT devices to Amazon Kinesis Data Streams. They want to process this data with an AWS Lambda function. Which configuration should be used to enable the Lambda function to be called automatically for processing the data in the stream?

Select 1 option(s):

Set up an Amazon S3 Event Notification to trigger the Lambda function.

Create a Kinesis Data Firehose delivery stream to invoke the Lambda function.

Configure the Kinesis Data Streams as a trigger for the Lambda function.

Use Amazon EC2 Auto Scaling to trigger the Lambda function.

Q52. A financial institution is using Amazon RDS for storing transaction data. They need to anonymize certain fields in the database for analysis while retaining the datas utility. Which approach would be most effective for achieving this?

Select 1 option(s):

Enable RDS encryption at rest to anonymize sensitive fields.

Use AWS Glue DataBrew to apply transformations for data anonymization.

Implement Amazon QuickSight‘s ML-powered insights for automatic data anonymization.

Apply AWS Shield for advanced protection and anonymization of data.

Q53. An organization is using AWS S3 to store confidential documents. They are evaluating whether to use client-side encryption or server-side encryption with S3. Which of the following considerations is most relevant when choosing between these two encryption options?

Select 1 option(s):

Client-side encryption provides better integration with AWS IAM for access control than server-side encryption.

Server-side encryption with AWS KMS provides automatic rotation of encryption keys, which is not available with client-side encryption.

Server-side encryption is the only method that allows for encryption of data in transit to S3.

Client-side encryption requires additional configuration on S3 to enable encryption at rest.

Q54. A data engineer is working with an AWS Glue workflow that uses multiple AWS Glue jobs to transform and load data. The engineer needs to ensure that any errors or failures in the workflow are quickly identified and can trigger automated actions. Which AWS service can the engineer use to set up alarms and notifications based on the workflows performance and errors?

Select 1 option(s):

AWS Data Pipeline

AWS Lambda

Amazon CloudWatch Alarms

Amazon Elastic MapReduce (EMR)

Q55. A data engineer is responsible for automating data processing tasks using AWS services. They need to ensure that data processing tasks are triggered by specific events and can scale based on demand. Which AWS service should they use for this purpose?

Select 1 option(s):

AWS Lambda

Amazon SQS (Simple Queue Service)

Amazon SNS (Simple Notification Service)

AWS Glue

Q56. An environmental research organization wants to consolidate various data sets, including satellite imagery, weather patterns, and environmental impact studies, for advanced analytics and machine learning. The solution must support diverse data formats and enforce strict access and governance policies. Which AWS service should they choose?

Select 1 option(s):

AWS Lake Formation

Amazon S3

Amazon EMR

Amazon Kinesis

Q57. A company needs to ingest large datasets from on-premises servers to Amazon S3 every night at 2 AM for further processing with AWS analytics services. Which AWS service should they use to automate and manage this scheduled batch data ingestion?

Select 1 option(s):

AWS Lambda

Amazon EC2

AWS Data Pipeline

Amazon Kinesis Data Firehose

Q58. A healthcare company wants to analyze patient data stored in Amazon S3 using AWS services, while ensuring that the patients identities remain anonymous. Which of the following techniques should they use for data anonymization before processing the data?

Select 1 option(s):

Implement AWS WAF to filter out sensitive information.

Use AWS Macie for automatic discovery and masking of personal data.

Apply Amazon Redshift Spectrum for on-the-fly anonymization of query results.

Utilize AWS Lambda to manually script and execute data anonymization processes.

Q59. An organization needs to securely connect their on-premises network to their AWS VPC and ensure that the data transmission is encrypted. Which VPC security networking concept should they utilize to meet these requirements?

Select 1 option(s):

Create a Network Address Translation (NAT) gateway for secure and encrypted data transmission.

Set up a Virtual Private Gateway and establish a VPN connection to the VPC.

Deploy an Internet Gateway in the VPC for encrypted connectivity to the on-premises network.

Use a VPC Peering connection to securely connect the on-premises network to the VPC.

AWS Data Engineer Associate - Test 11

Q2. A retail company wants to process and analyze streaming data from point-of-sale (POS) systems across various stores in real-time. Which AWS service is best suited for efficiently ingesting and processing this streaming data?

Q4. A retail company wants to analyze customer purchase behavior by processing transaction data in real-time. The solution should be capable of handling continuous data streams and provide timely insights. Which AWS service is the best choice for this requirement?

Q5. An e-commerce company needs to regularly ingest and transform large volumes of sales data stored in Amazon S3 into a format suitable for analysis. The ingestion process should be automated and occur daily. Which AWS service is best suited for this batch data ingestion and transformation task?

Q6. A media company needs to analyze web server logs stored in CSV format. The analysis involves complex queries and joins. The data is not frequently accessed but needs to be available for ad-hoc queries. Which combination of AWS services is most appropriate for this use case?

Q7. Your team is building a real-time analytics system that requires low-latency data ingestion. Which AWS service is most suitable for this requirement, particularly considering throughput and latency characteristics?

Q8. A company is migrating its on-premises legacy database to AWS. The database primarily handles OLTP workloads and requires high availability and consistent performance. Which AWS service is the most suitable for this migration?

Q9. An enterprise needs to aggregate, catalog, and securely store data coming from various sources such as IoT devices, social media, and transactional systems. The solution should facilitate data analysis and governance. Which AWS service would best meet these requirements?

Q10. A company needs to ingest large volumes of data from various sources at high throughput. Which AWS service should they choose to meet these throughput and latency characteristics?

Q11. A financial institution requires a data storage solution to perform real-time analytics on transactional data. The data needs to be frequently updated and queried. Which AWS service is most appropriate to meet these specific access patterns and performance requirements?

Q12. Your company is setting up a data lake on AWS for storing large-scale analytics data. The data is in Apache Parquet format and will be used for complex ad-hoc queries. Which AWS service is the most suitable for this purpose?

Q13. A media streaming company is using Amazon S3 to store and distribute video content to users. They want to ensure that all data transferred from S3 to the users devices is encrypted during transit. Which AWS service or feature should they enable to achieve this goal effectively?

Q15. A healthcare analytics company needs to ensure that their data ingestion pipeline can reprocess data in case of failures or updates in processing logic. Which AWS service would be most effective for enabling replayability of data in their ingestion pipeline?

Q16. A data engineer is designing an automated data processing pipeline that requires running containerized tasks without the need to manage the underlying infrastructure. They want to ensure scalability and flexibility in their solution. Which AWS service is suitable for this use case?

Q17. A data engineer is responsible for maintaining a data processing workflow that includes multiple AWS services. They want to automate error detection and notification in the workflow to ensure it runs smoothly. Which AWS service or feature should they use for this purpose?

Q18. A company wants to automatically process new images uploaded to an Amazon S3 bucket and generate thumbnails. Which service should be used to trigger a thumbnail generation function each time a new image is uploaded to the bucket?

Q19. In an application deployed on AWS, sensitive data is being stored in an Amazon DynamoDB table. To enhance data security, the team decides to implement key salting techniques. Which of the following methods should they adopt for effective key salting in this scenario?

Q20. Your organization needs to store a large volume of sensor data collected from IoT devices. The data will be ingested continuously and needs to be available for frequent access and analysis. Which AWS storage service would be most appropriate?

Q21. In an Amazon Redshift environment, a team needs to perform maintenance tasks without risking data integrity due to concurrent write operations. What should they implement to prevent write access to specific tables during maintenance?

Q24. A data engineer is building a data processing pipeline using AWS services. They need to ensure that API calls for data processing tasks are monitored, logged, and can be audited for security and compliance purposes. Which AWS service should they use for this requirement?

Q27. A data engineer is building an automated ETL (Extract, Transform, Load) pipeline that needs to execute code in response to changes in Amazon S3 buckets. They want to ensure that the code runs without provisioning or managing servers. Which AWS service can meet this requirement?

Q29. An organization uses AWS Glue for data processing and needs to ensure that their script logs, stored in Amazon CloudWatch, are encrypted. What is the most effective method to achieve this?

Q30. A data engineer needs to ingest data from a third-party service that exposes a REST API, updating every 30 minutes. The data needs to be stored in AWS for analysis. Which AWS service should be used to consume the data API and ingest the data efficiently?

Q31. A data engineering team is implementing a password storage system on AWS. They want to enhance the security of the stored passwords by using key salting techniques. Which of the following approaches should they use to incorporate key salting effectively?

Q32. A company is planning to deploy a data storage solution on AWS and is considering between Amazon S3 (a managed service) and setting up a file storage system on Amazon EC2 instances (an unmanaged service). What is a key difference in terms of authentication mechanisms between these two options?

Q33. A data engineer is setting up a batch ingestion pipeline to transfer large datasets from an on-premises database to Amazon Redshift nightly. Which configuration option would optimize the data transfer performance?

Q34. A data engineer is tasked with processing large volumes of log data stored in Amazon S3. The engineer needs to perform distributed data processing and analysis using a managed service. Which AWS service should the engineer choose to efficiently process this data?

Q35. An application logs user activity data to an Amazon S3 bucket. A data engineer needs to set up a system to analyze these logs in near-real-time. Which AWS service should be used to trigger the analysis process each time a new log file is written to the S3 bucket?

Q36. A research team needs to store a vast amount of environmental data collected from sensors. The data is in plain text (.txt) format and will be used for occasional complex analytics. Which AWS service is the most appropriate for storing and processing this data?

Q40. A company is using AWS Glue for their ETL processes. They need to ensure that the data stored in the AWS Glue Data Catalog is encrypted. Which of the following options should be used to meet this requirement?

Q41. A company needs to store and regularly process log files generated by their application. The logs are in text format and the processing involves searching and filtering operations. Which combination of AWS services should be used to efficiently store and process this data?

Q43. A company needs to store relational data with high transaction rates and requires immediate consistency. The data will be used for online transaction processing (OLTP). Which AWS service should be used?

Q44. Your company requires a storage solution for large-scale, unstructured data that can be accessed globally with low latency. The data is frequently accessed and requires high durability. Which AWS storage solution is most suitable?

Q45. An e-commerce platform needs to ingest user activity data from its website at the end of each day, process the data, and then load it into Amazon Redshift for analysis. Which AWS service combination is most appropriate for this batch data ingestion and processing?

Q46. A startup is developing a new online booking system that requires a database to handle frequent read and write operations with high availability and automated backups. The database should also allow for easy scaling as the user base grows. Which AWS service should be used for this scenario?

Q47. A financial services company needs to ensure that personally identifiable information (PII) in their Amazon DynamoDB tables is masked when accessed by certain users. Which approach is most appropriate for masking this data in DynamoDB?

Q48. A data engineer wants to set up a complex workflow that involves triggering multiple AWS Glue crawlers and ETL jobs in a specific sequence. The workflow should run every week. Which tool is most suitable for orchestrating and scheduling this workflow?

Q49. A data engineer is working on a project that requires running custom scripts for data processing. They need a service that accepts scripting for tasks like data transformation and analysis. Which AWS service should they choose for this purpose?

Q50. A company is using Amazon RDS to store customer data. For compliance reasons, they need to mask credit card information in their database before providing access to their analytics team. Which AWS service or feature should they use to achieve this requirement effectively?

Q51. A company is streaming real-time data from IoT devices to Amazon Kinesis Data Streams. They want to process this data with an AWS Lambda function. Which configuration should be used to enable the Lambda function to be called automatically for processing the data in the stream?

Q52. A financial institution is using Amazon RDS for storing transaction data. They need to anonymize certain fields in the database for analysis while retaining the datas utility. Which approach would be most effective for achieving this?

Q53. An organization is using AWS S3 to store confidential documents. They are evaluating whether to use client-side encryption or server-side encryption with S3. Which of the following considerations is most relevant when choosing between these two encryption options?

Q55. A data engineer is responsible for automating data processing tasks using AWS services. They need to ensure that data processing tasks are triggered by specific events and can scale based on demand. Which AWS service should they use for this purpose?

Q57. A company needs to ingest large datasets from on-premises servers to Amazon S3 every night at 2 AM for further processing with AWS analytics services. Which AWS service should they use to automate and manage this scheduled batch data ingestion?

Q58. A healthcare company wants to analyze patient data stored in Amazon S3 using AWS services, while ensuring that the patients identities remain anonymous. Which of the following techniques should they use for data anonymization before processing the data?

Q59. An organization needs to securely connect their on-premises network to their AWS VPC and ensure that the data transmission is encrypted. Which VPC security networking concept should they utilize to meet these requirements?

Q13. A media streaming company is using Amazon S3 to store and distribute video content to users. They want to ensure that all data transferred from S3 to the users devices is encrypted during transit. Which AWS service or feature should they enable to achieve this goal effectively?

Q52. A financial institution is using Amazon RDS for storing transaction data. They need to anonymize certain fields in the database for analysis while retaining the datas utility. Which approach would be most effective for achieving this?

Q58. A healthcare company wants to analyze patient data stored in Amazon S3 using AWS services, while ensuring that the patients identities remain anonymous. Which of the following techniques should they use for data anonymization before processing the data?