Amazon Data-Engineer-Associate Korean Valid Q&A - in .pdf

  • Data-Engineer-Associate Korean pdf
  • Exam Code: Data-Engineer-Associate Korean
  • Exam Name: AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate Korean Version)
  • Updated: May 31, 2026
  • Q & A: 290 Questions and Answers
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  • Exam Code: Data-Engineer-Associate Korean
  • Exam Name: AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate Korean Version)
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  • Q & A: 290 Questions and Answers
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Data-Engineer-Associate Korean pass review

Amazon AWS Certified Data Engineer - Associate (DEA-C01) (Data-Engineer-Associate Korean Version) Sample Questions:

1. 어떤 회사는 제3자로부터 온 고객 데이터를 Amazon Redshift 데이터 웨어하우스에 로드해야 합니다. 이 회사는 주문 데이터와 제품 데이터를 동일한 데이터 웨어하우스에 저장합니다. 이 회사는 결합된 데이터 세트를 사용하여 잠재적 신규 고객을 식별하려고 합니다.
데이터 엔지니어는 소스 데이터의 필드 중 하나에 JSON 형식의 값이 포함되어 있음을 발견했습니다.
데이터 엔지니어는 최소한의 노력으로 JSON 데이터를 데이터 웨어하우스에 로드하려면 어떻게 해야 할까요?

A) SUPER 데이터 유형을 사용하여 Amazon Redshift 테이블에 데이터를 저장합니다.
B) AWS Glue를 사용하여 JSON 데이터를 평면화하고 Amazon Redshift 테이블에 수집합니다.
C) AWS Lambda 함수를 사용하여 JSON 데이터를 평면화합니다. Amazon S3에 데이터를 저장합니다.
D) Amazon S3를 사용하여 JSON 데이터를 저장합니다. Amazon Athena를 사용하여 데이터를 쿼리합니다.


2. 한 회사는 MySQL용 Amazon RDS를 중요한 애플리케이션의 데이터베이스로 사용합니다. 데이터베이스 워크로드는 대부분 쓰기이며 읽기 횟수는 적습니다.
데이터 엔지니어는 DB 인스턴스의 CPU 사용률이 매우 높다는 사실을 발견했습니다. CPU 사용률이 높으면 애플리케이션 속도가 느려집니다. 데이터 엔지니어는 DB 인스턴스의 CPU 사용률을 줄여야 합니다.
이 요구 사항을 충족하려면 데이터 엔지니어가 어떤 조치를 취해야 합니까? (2개를 선택하세요.)

A) 추가 테이블과 인덱스를 포함하도록 데이터베이스 스키마를 수정합니다.
B) 매주 한 번씩 RDS DB 인스턴스를 재부팅합니다.
C) 데이터베이스 쿼리 로드를 줄이기 위해 캐싱을 구현합니다.
D) Amazon RDS의 성능 개선 도우미 기능을 사용하여 CPU 사용률이 높은 쿼리를 식별합니다.
문제가 있는 쿼리를 최적화합니다.
E) 더 큰 인스턴스 크기로 업그레이드합니다.


3. 글로벌 전자상거래 기업에서 고객 거래, 재고 업데이트, 사용자 활동 로그 등을 여러 AWS 서비스를 통해 처리합니다. 이 회사는 복잡한 ETL(추출, 변환, 로드) 워크플로우를 효율적으로 관리하기 위한 확장 가능하고 완전 관리형 이벤트 기반 오케스트레이션 솔루션이 필요합니다. 데이터 처리를 위해 AWS Glue와 Amazon EMR을 활용해야 하며, 데이터는 Amazon Redshift와 Amazon S3에 저장됩니다. 또한, 종속성 관리, 자동 재시도, 데이터 파이프라인 모니터링 기능을 지원해야 합니다.
어떤 솔루션이 이러한 요구 사항을 충족할까요?

A) AWS Step Functions를 사용하여 Amazon EMR 및 AWS Glue에서 데이터 변환 및 로딩 작업을 호출하는 Express 워크플로를 정의합니다.
B) 워크플로의 각 단계에 대한 AWS Lambda 함수를 생성합니다. AWS Glue 작업을 호출하도록 Amazon EventBridge를 구성합니다. 파이프라인을 통해 데이터를 처리하고 이동하도록 Lambda 함수를 구성합니다.
C) 워크플로의 각 단계를 실행하는 AWS Lambda 함수를 생성합니다. 매일 해당 함수를 호출하도록 Amazon EventBridge 예약 규칙을 생성합니다.
D) ETL 워크플로우를 관리하기 위해 방향 비순환 그래프(DAG)를 생성하려면 Amazon Managed Workflows for Apache Airflow(Amazon MWAA)에서 Apache Airflow를 사용하십시오.


4. 회사에서 온프레미스 워크로드를 AWS로 마이그레이션하고 있습니다. 회사는 전반적인 운영 오버헤드를 줄이고 싶어합니다. 또한 회사는 서버리스 옵션도 살펴보고 싶어합니다.
회사의 현재 워크로드는 Apache Pig, Apache Oozie, Apache Spark, Apache Hbase 및 Apache Flink를 사용합니다. 온프레미스 워크로드는 페타바이트 규모의 데이터를 몇 초 만에 처리합니다. 회사는 AWS로 마이그레이션한 후에도 유사하거나 더 나은 성능을 유지해야 합니다.
이러한 요구 사항을 충족하는 ETL(추출, 변환 및 로드) 서비스는 무엇입니까?

A) Amazon Redshift
B) Amazon EMR
C) AWS 람다
D) AWS Glue


5. 한 회사는 데이터 웨어하우스로 Amazon Redshift를 사용합니다. 회사는 Amazon Redshift 구체화된 뷰에 대한 새로 고침 일정을 자동화해야 합니다.
최소한의 노력으로 이 요구 사항을 충족할 수 있는 솔루션은 무엇입니까?

A) AWS Glue 워크플로를 사용하여 구체화된 뷰를 새로 고칩니다.
B) Apache Airflow를 사용하여 구체화된 뷰를 새로 고칩니다.
C) Amazon Redshift의 쿼리 편집기 v2를 사용하여 구체화된 뷰를 새로 고칩니다.
D) Amazon Redshift 내에서 AWS Lambda 사용자 정의 함수(UDF)를 사용하여 구체화된 보기를 새로 고칩니다.


Solutions:

Question # 1
Answer: A
Question # 2
Answer: C,D
Question # 3
Answer: D
Question # 4
Answer: B
Question # 5
Answer: D

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