Amazon Web ServicesAssociate levelDEA-C01Page 2 of 6

DEA-C01 exam dumps: questions 101 to 200 of 549

Page 2 of the free DEA-C01 question bank for the AWS Certified Data Engineer - Associate exam. Questions 101 to 200 are listed below, the first 5 in full with answers and explanations. Back to page 1 for the exam overview and FAQ.

Question bank last updated December 2024

Start timed practice exam Questions 101 to 200

Free DEA-C01 practice questions

Questions 101 to 105 of 549

Pick an answer before you open the explanation. Each question also has its own page with a permalink.

DEA-C01 Question 101

Select 2

You are tasked with designing a serverless workflow to process images uploaded to an S3 bucket. The workflow should trigger automatically when a new image is uploaded, resize the image using AWS Lambda, and store the resized image in another S3 bucket. You want to ensure the workflow is both scalable and cost-effective. Which combination of AWS services should you use to achieve this?

  1. A

    Amazon S3 event notifications to trigger an AWS Lambda function

  2. B

    AWS Step Functions to orchestrate the workflow

  3. C

    Amazon DynamoDB to store metadata about the resized images

  4. D

    AWS Lambda to resize the images

  5. E

    Amazon SQS to queue the image processing tasks

Show answer and explanation

Correct answers: A, D

Explanation

The combination of Amazon S3 event notifications and AWS Lambda provides a serverless and event-driven workflow to handle image uploads and resizing. This approach is scalable, cost-effective, and eliminates the need for additional orchestration or queuing services. S3 notifications automatically trigger the Lambda function to process the images, and Lambda handles the resizing operation efficiently.

  • A. Correct.

    Correct. Amazon S3 event notifications can be configured to trigger an AWS Lambda function whenever a new image is uploaded, making it an ideal serverless and event-driven solution.

  • B. Incorrect.

    Incorrect. While AWS Step Functions can be used for workflow orchestration, it is unnecessary in this scenario because the workflow only involves a single Lambda function triggered directly by an S3 event.

  • C. Incorrect.

    Incorrect. Amazon DynamoDB is not required here since the scenario does not mention a need to store metadata about the resized images.

  • D. Correct.

    Correct. AWS Lambda is a serverless compute service that can resize the images as part of the workflow, making it both scalable and cost-effective.

  • E. Incorrect.

    Incorrect. Amazon SQS is not needed because this scenario focuses on direct event-driven processing rather than queuing tasks for asynchronous execution.

DEA-C01 Question 102

Single answer

You are designing a serverless data processing pipeline for a video streaming application. The pipeline involves extracting metadata from uploaded videos, storing the metadata in a database, and notifying users when processing is complete. The solution must be highly scalable, cost-effective, and must not require server management. Which AWS service combination is best suited to orchestrate this workflow in a serverless manner?

  1. A

    AWS Step Functions, AWS Lambda, Amazon DynamoDB, and Amazon SNS

  2. B

    Amazon EC2, AWS Lambda, Amazon RDS, and Amazon SQS

  3. C

    AWS Glue, Amazon S3, Amazon RDS, and Amazon SNS

  4. D

    Amazon EMR, Amazon DynamoDB, AWS Step Functions, and Amazon SQS

Show answer and explanation

Correct answer: A

Explanation

The best approach to create a fully serverless and scalable workflow involves using AWS Step Functions for orchestration, AWS Lambda for executing the metadata extraction, Amazon DynamoDB for storing the metadata, and Amazon SNS for notifying users. This combination aligns with the requirements of being cost-effective, serverless, and scalable.

  • A. Correct.

    This is the correct answer. AWS Step Functions can be used to orchestrate the workflow as a serverless state machine. AWS Lambda handles the metadata extraction, Amazon DynamoDB stores the metadata, and Amazon SNS notifies users, all in a scalable and serverless manner.

  • B. Incorrect.

    This is incorrect. While AWS Lambda is serverless, Amazon EC2 and Amazon RDS involve server management, which does not align with the requirement of a fully serverless solution.

  • C. Incorrect.

    This is incorrect. AWS Glue and Amazon S3 are primarily used for ETL and data storage, respectively, and are not ideal for orchestrating a serverless workflow. Amazon RDS is also not serverless.

  • D. Incorrect.

    This is incorrect. Amazon EMR is not serverless and is overkill for the described task. While AWS Step Functions and Amazon DynamoDB are suitable, Amazon SQS is not ideal for user notifications in this scenario.

DEA-C01 Question 103

Select 3

You are designing a serverless data processing workflow to process images uploaded to an Amazon S3 bucket. The workflow should automatically trigger on new object uploads, perform image analysis using Amazon Rekognition, and store the results in an Amazon DynamoDB table. Which combination of AWS services and features should you use to implement this workflow?

  1. A

    Use Amazon S3 event notifications to trigger an AWS Lambda function.

  2. B

    Configure the AWS Lambda function to invoke Amazon Rekognition for image analysis.

  3. C

    Set up an Amazon S3 Lifecycle policy to process images and store results in DynamoDB.

  4. D

    Use Amazon EventBridge to directly trigger Amazon Rekognition on S3 object uploads.

  5. E

    Configure the AWS Lambda function to store analysis results in the Amazon DynamoDB table.

Show answer and explanation

Correct answers: A, B, E

Explanation

To design a serverless workflow, Amazon S3 event notifications can trigger an AWS Lambda function when a new image is uploaded. The Lambda function can then invoke Amazon Rekognition for image analysis and store the results in an Amazon DynamoDB table. This combination ensures the workflow is automated, scalable, and serverless.

  • A. Correct.

    Correct: Amazon S3 event notifications can trigger an AWS Lambda function when a new object is created in the S3 bucket, making this a key component of the workflow.

  • B. Correct.

    Correct: The AWS Lambda function can use the Amazon Rekognition API to perform image analysis, aligning with the requirement.

  • C. Incorrect.

    Incorrect: Amazon S3 Lifecycle policies are used for managing object lifecycle transitions (e.g., moving to a different storage class or deletion), not for triggering workflows or processing images.

  • D. Incorrect.

    Incorrect: Amazon EventBridge cannot directly invoke Amazon Rekognition. EventBridge can route and manage events, but it does not handle image analysis tasks.

  • E. Correct.

    Correct: The AWS Lambda function can insert the analysis results into the DynamoDB table, fulfilling the requirement to store the results.

DEA-C01 Question 104

Select 2

You are tasked with designing a serverless data processing workflow for a retail company. The workflow involves processing customer order data stored in an Amazon S3 bucket, performing data transformations, and loading the processed data into an Amazon Redshift table for analytics. Which combination of services can you use to build this serverless workflow efficiently?

  1. A

    AWS Step Functions to orchestrate the workflow, AWS Lambda for data transformation, and Amazon Redshift COPY command for loading data

  2. B

    AWS Glue for data transformation, Amazon EMR for orchestration, and Amazon Redshift COPY command for loading data

  3. C

    AWS Step Functions to orchestrate the workflow, AWS Glue for data transformation, and Amazon Redshift COPY command for loading data

  4. D

    Amazon Kinesis Data Firehose for orchestration, AWS Glue for data transformation, and Amazon Redshift COPY command for loading data

  5. E

    AWS Lambda to orchestrate the workflow, AWS Glue for data transformation, and Amazon Redshift COPY command for loading data

Show answer and explanation

Correct answers: A, C

Explanation

Serverless workflows leverage services that do not require infrastructure management. AWS Step Functions is ideal for orchestrating serverless workflows, while AWS Lambda and AWS Glue can handle data transformation. The Amazon Redshift COPY command is optimized for loading data. Combining these services creates a scalable, cost-effective solution for serverless data processing workflows.

  • A. Correct.

    Correct: AWS Step Functions is a serverless orchestration service, AWS Lambda can transform the data, and the Amazon Redshift COPY command efficiently loads data into Redshift, making this a valid solution.

  • B. Incorrect.

    Incorrect: Amazon EMR is not serverless and is not suitable for orchestrating a fully serverless workflow.

  • C. Correct.

    Correct: AWS Step Functions is a serverless orchestration service, AWS Glue can handle data transformation, and the Amazon Redshift COPY command efficiently loads data into Redshift, making this another valid solution.

  • D. Incorrect.

    Incorrect: Amazon Kinesis Data Firehose is designed for streaming data delivery, not for workflow orchestration, so this is not a valid solution.

  • E. Incorrect.

    Incorrect: AWS Lambda is not designed to orchestrate workflows; AWS Step Functions or other orchestration tools should be used for this purpose.

DEA-C01 Question 105

Single answer

You are designing a serverless data processing workflow for a real-time analytics application. The workflow needs to ingest streaming data from Amazon Kinesis Data Streams, process the data, and store the results in Amazon S3. The processing logic requires orchestration of multiple steps, including data transformation and error handling. Which AWS service should you use to build and manage this workflow?

  1. A

    AWS Step Functions

  2. B

    Amazon EMR

  3. C

    AWS Glue

  4. D

    Amazon SNS

Show answer and explanation

Correct answer: A

Explanation

AWS Step Functions is a serverless orchestration service that allows you to build complex workflows by coordinating multiple AWS services. In this scenario, Step Functions can manage the entire workflow by connecting the Kinesis Data Streams for ingestion, invoking Lambda functions for data transformation, and storing the results in Amazon S3. Additionally, it provides built-in error handling and supports integration with other AWS services, making it the most suitable solution for this use case.

  • A. Correct.

    AWS Step Functions is the correct choice for orchestrating serverless workflows. It allows you to define complex workflows with multiple steps, including error handling, and integrates seamlessly with AWS services like Kinesis, S3, and Lambda.

  • B. Incorrect.

    Amazon EMR is used primarily for big data processing using frameworks like Hadoop and Spark. It is not a serverless orchestration service and is not suitable for managing complex workflows.

  • C. Incorrect.

    AWS Glue is an ETL (Extract, Transform, Load) service designed for data preparation and transformation. While it supports certain workflows, it is not intended for orchestrating serverless workflows in the way AWS Step Functions is.

  • D. Incorrect.

    Amazon SNS is a messaging service for pub/sub communication. While it can be used in workflows, it does not provide the orchestration capabilities required for managing complex serverless workflows.

Timed practice exam

Take a DEA-C01 practice test under exam conditions

65 questions in 130 minutes, drawn from this bank, with a score report and a per-question review when you finish.

Start timed exam

DEA-C01 practice questions 101 to 200 of 549

Every question has a page with the answer and explanation. Numbers are stable, so you can bookmark or share them. The bank is split into 6 pages of up to 100 questions.

  1. 101.You are tasked with designing a serverless workflow to process images uploaded to an S3 bucket. The workflow...
  2. 102.You are designing a serverless data processing pipeline for a video streaming application. The pipeline...
  3. 103.You are designing a serverless data processing workflow to process images uploaded to an Amazon S3 bucket....
  4. 104.You are tasked with designing a serverless data processing workflow for a retail company. The workflow...
  5. 105.You are designing a serverless data processing workflow for a real-time analytics application. The workflow...
  6. 106.You are working on a data engineering project where you need to process a large amount of data stored in...
  7. 107.You are working on a data processing pipeline using AWS Glue. Your task is to transform a large dataset...
  8. 108.You are designing a data pipeline using AWS Glue to transform raw sales data into a structured format stored...
  9. 109.A company processes streaming data from IoT sensors using AWS Kinesis Data Streams. You need to implement a...
  10. 110.You are tasked with designing a data pipeline for processing clickstream data from a website. The data is...
  11. 111.You are designing a data pipeline to process and store clickstream data from a website in real-time. The data...
  12. 112.You are designing a data pipeline in AWS to process streaming data from IoT devices. The data needs to be...
  13. 113.You are working as a Data Engineer at an e-commerce company. The company collects real-time clickstream data...
  14. 114.You are working as a Data Engineer for an e-commerce company. The company uses Amazon Kinesis Data Streams to...
  15. 115.You are working as a data engineer for a company that processes large-scale clickstream data. The data is...
  16. 116.You are managing a data engineering team that builds and deploys ETL pipelines on AWS. Your team has adopted...
  17. 117.You are a data engineer building an end-to-end data pipeline using AWS services. The pipeline ingests...
  18. 118.You are tasked with implementing a CI/CD pipeline for a data engineering team that processes large datasets...
  19. 119.You are designing a CI/CD pipeline for deploying data pipelines in AWS. Your team wants to automate the...
  20. 120.Your company has implemented a CI/CD pipeline for deploying AWS Glue jobs that process large datasets stored...
  21. 121.You are working as a data engineer at a company that uses Amazon Redshift for their data warehouse. You are...
  22. 122.You are a data engineer at a company that uses Amazon Redshift for its data warehouse. The marketing team has...
  23. 123.You are working as a data engineer for an e-commerce company. You need to transform raw data stored in an...
  24. 124.You are working as a data engineer for a company that processes large volumes of e-commerce transactions. The...
  25. 125.You are working as a Data Engineer at an e-commerce company. You are tasked with querying data from an Amazon...
  26. 126.You are a data engineer tasked with deploying an Amazon Redshift cluster along with its associated IAM roles...
  27. 127.You are a data engineer tasked with deploying an Amazon Redshift cluster for your organization. The...
  28. 128.You are tasked with deploying an Amazon Redshift cluster to multiple environments (development, staging, and...
  29. 129.You are a data engineer responsible for deploying an Amazon EMR cluster as part of your company's data...
  30. 130.You are designing an automated deployment pipeline for a data processing application on AWS. The pipeline...
  31. 131.You are working as a data engineer for a company that processes large datasets daily. The company uses Amazon...
  32. 132.You are designing a distributed data processing pipeline for an e-commerce platform that processes terabytes...
  33. 133.You are working as a Data Engineer for a company that processes large-scale sensor data from IoT devices....
  34. 134.A data engineering team is using Amazon EMR to process a large dataset stored in Amazon S3. The team notices...
  35. 135.You are designing a distributed data processing solution on AWS to process vast amounts of data from IoT...
  36. 136.You are designing a data pipeline for a social networking application. The application needs to recommend new...
  37. 137.You are building a recommendation system for an e-commerce platform on AWS. The system needs to identify...
  38. 138.A company uses Amazon Neptune to store and query their graph-based social network data. They want to find the...
  39. 139.A social media platform is using Amazon Neptune to store and analyze its user relationships. The platform...
  40. 140.You are working on a recommendation system for an e-commerce platform using AWS Neptune, and you need to...
  41. 141.You are working as a Data Engineer for a company using Amazon Redshift for their data warehouse. You notice...
  42. 142.You are working as a data engineer for a company that uses Amazon Redshift as their data warehouse. One of...
  43. 143.You are working as a data engineer for an e-commerce company that stores its transactional data in Amazon...
  44. 144.A data engineering team is using Amazon Redshift to analyze a large dataset stored in a table with billions...
  45. 145.You are working with Amazon Redshift to analyze a large dataset stored in a table called 'sales'. The table...
  46. 146.You are designing a data processing pipeline to analyze e-commerce transaction data. The data must be stored...
  47. 147.A company is building a real-time stock trading application that requires low-latency access to data and...
  48. 148.Your company is building a data lake on AWS to store and analyze large volumes of structured and unstructured...
  49. 149.Your company is building a data lake on Amazon S3 to store raw, semi-structured, and structured data. You...
  50. 150.Your company is building a data lake on Amazon S3 to store and analyze terabytes of semi-structured data. You...
  51. 151.A company is building a real-time analytics dashboard for its e-commerce platform. The dashboard must process...
  52. 152.Your company is building a real-time analytics platform to process millions of IoT sensor events per second....
  53. 153.A company is building a real-time analytics platform to process clickstream data from their website. The data...
  54. 154.A retail company processes incoming transactional data from their point-of-sale systems in real-time. They...
  55. 155.A company needs to store large volumes of semi-structured data generated by an IoT fleet of sensors. The data...
  56. 156.You are designing a data processing pipeline on AWS to analyze large-scale streaming data from IoT devices....
  57. 157.You are designing a data pipeline to process streaming data from IoT devices that send temperature readings...
  58. 158.You are tasked with designing a data pipeline to process large volumes of streaming event data generated by...
  59. 159.You are tasked with designing a data pipeline in AWS to process large volumes of real-time streaming data...
  60. 160.Your organization needs to process a large volume of semi-structured data stored in Amazon S3, and the...
  61. 161.You are designing a data lake architecture for a large e-commerce company. The system must handle a mix of...
  62. 162.A company needs to store both structured and unstructured data for their data lake. They also require...
  63. 163.A data engineering team is tasked with building a scalable data lake for storing and analyzing both...
  64. 164.A retail company wants to build a data lake to store and analyze large volumes of structured,...
  65. 165.You are designing a data lake for your organization to store and analyze a large volume of structured,...
  66. 166.Your team is building a data lake on Amazon S3 to store large-scale analytical data. The data will be queried...
  67. 167.A data engineering team is building a real-time analytics pipeline that processes high-frequency financial...
  68. 168.A data engineering team is tasked with storing a high-volume data stream from IoT devices. The team requires...
  69. 169.A data engineering team is responsible for managing a high-performance analytics workload that requires...
  70. 170.You are working as a data engineer for a company that processes large-scale IoT sensor data. The raw data is...
  71. 171.You are designing a data pipeline to process large volumes of semi-structured data in AWS. The data will be...
  72. 172.You are designing a data pipeline in AWS that processes large volumes of semi-structured data. The pipeline...
  73. 173.You are designing a data pipeline in AWS to process large volumes of data stored in Amazon S3. The data will...
  74. 174.A data engineering team is processing a large volume of IoT sensor data and needs to store it in Amazon S3...
  75. 175.A data engineering team is designing a data pipeline for a large-scale analytics workload. The pipeline...
  76. 176.A company is planning to migrate its on-premises data warehouse to AWS. Their existing data is structured and...
  77. 177.Your company is planning to migrate its on-premises data warehouse to AWS. The data consists of structured...
  78. 178.A company wants to migrate their on-premises data warehouse to AWS. Their data consists of structured tables...
  79. 179.A company is migrating its on-premises data warehouse to AWS and needs to ensure the data storage solution...
  80. 180.You are tasked with migrating a large on-premises data warehouse to AWS. The data consists of structured and...
  81. 181.You are designing a data pipeline for a company that needs to store and process customer transaction logs....
  82. 182.A data engineering team is building a data lake for an e-commerce platform. They need to store clickstream...
  83. 183.You are designing a data storage solution for an e-commerce platform that tracks user interactions. The...
  84. 184.A data engineering team is designing a data storage solution for a financial analytics platform. The platform...
  85. 185.A company is designing a data lake architecture on AWS to store and analyze large volumes of data from...
  86. 186.You are a data engineer managing an Amazon Redshift cluster for a data analytics team. Analysts frequently...
  87. 187.You are designing a data processing pipeline using Amazon Redshift to handle large-scale analytics. During...
  88. 188.You are designing a data processing workflow for a company using Amazon Redshift and Amazon RDS. To prevent...
  89. 189.You are designing a data processing workflow that uses Amazon Redshift for analytics. Your team has reported...
  90. 190.You are a data engineer managing an Amazon Redshift cluster for a data analytics team. The team reports that...
  91. 191.A data engineering team is setting up an analytics pipeline using AWS Glue. They need to ensure that all...
  92. 192.Your company uses AWS Glue as a data integration service. The team has recently onboarded multiple data...
  93. 193.A data engineering team is tasked with building a data lake on Amazon S3. They want to ensure that all...
  94. 194.Your organization uses Amazon S3 to store large volumes of data and Amazon Athena for querying the data. To...
  95. 195.A data engineering team is building a data lake on Amazon S3 and wants to enable users to easily discover and...
  96. 196.You are working as a Data Engineer for a company that collects IoT sensor data from devices deployed...
  97. 197.You are tasked with designing a real-time streaming data pipeline for a financial services company to process...
  98. 198.You are a data engineer tasked with designing a real-time analytics pipeline for a stock trading platform....
  99. 199.An e-commerce company needs to analyze customer purchase behavior in real-time to provide personalized...
  100. 200.You are designing a data pipeline for a company that processes large volumes of clickstream data from its...

More AWS exam dumps

All AWS exams
AIF-C01230 questions

AWS Certified AI Practitioner exam dumps

AWS Certified AI Practitioner

ANS-C01512 questions

AWS Advanced Networking Specialty exam dumps

AWS Certified Advanced Networking - Specialty

CLF-C02341 questions

AWS Certified Cloud Practitioner exam dumps

AWS Certified Cloud Practitioner

DOP-C02410 questions

AWS DevOps Engineer Professional exam dumps

AWS Certified DevOps Engineer - Professional

DVA-C02398 questions

AWS Developer Associate exam dumps

AWS Certified Developer - Associate

MLS-C01388 questions

AWS Machine Learning Specialty exam dumps

AWS Certified Machine Learning - Specialty

MLA-C01457 questions

AWS Machine Learning Engineer Associate exam dumps

AWS Certified Machine Learning Engineer - Associate

SCS-C02503 questions

AWS Security Specialty exam dumps

AWS Certified Security - Specialty