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AWS (Amazon)

AWS Certified Data Engineer - Associate

The AWS Certified Data Engineer – Associate (DEA-C01) exam validates a candidate’s ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with AWS best practices.

Code examen

DEA-C01

Durée

180 min

Questions

65

Prérequis officiels

  • Hands-on experience with AWS core services: S3, EC2, IAM, VPC
  • Familiarity with data storage and analytics: RDS, Redshift, DynamoDB, Athena
  • Experience designing and implementing ETL/data pipelines using AWS Glue, Kinesis, or Data Pipeline
  • Proficiency in SQL and a scripting language such as Python or Scala
  • Understanding of security, networking, and cost optimization for cloud data solutions
AWS Certified Data Engineer - Associate

Professions ciblées

Data Engineer Cloud Data Engineer Big Data Engineer ETL Developer Data Platform Engineer
Articles connexes

Domaines clés

Le moteur de simulation d'ExamBoot est synchronisé avec le plan officiel de l'examen. Nos banques de questions adaptatives priorisent l'atteinte rapide de vos objectifs..

Understand different data storage types and design efficient architectures to store, retrieve, and manage data on AWS.
Implement Extract, Transform, Load (ETL) processes using AWS services to move and transform data, ensuring data reliability and efficiency.
Utilize AWS tools to analyze data and create visual representations, enabling enhanced data understanding and decision-making.
Implement security protocols and policies in AWS data services to ensure data protection, privacy, and compliance with regulations.
Apply best practices for monitoring, performance optimization, and maintenance in data engineering solutions on AWS.

un domaine 5

Operational Best Practices

15%
Apply best practices for monitoring, performance optimization, and maintenance in data engineering solutions on AWS.

Conseil d'étude

Practice hands-on labs with S3, Glue, Kinesis, Redshift, Athena; complete AWS whitepapers, sample exams, and build end-to-end data pipelines for real scenarios.

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