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NEW QUESTION: 1
情報セキュリティ管理者が上級管理職に定期的に報告するために最も重要なものは次のうちどれですか？
A. 監査レポート
B. 脅威分析レポート
C. 侵入テストの結果
D. 修正されていないリスクの影響
Answer: D
NEW QUESTION: 2
Key maintenance and security are paramount within a cloud environment due to the widespread use of encryption for both data and transmissions.
Which of the following key-management systems would provide the most robust control over and ownership of the key-management processes for the cloud customer?
A. Remote key management service
B. Internal key management service
C. Client key management service
D. Local key management service
Answer: A
Explanation:
A remote key management system resides away from the cloud environment and is owned and controlled by the cloud customer. With the use of a remote service, the cloud customer can avoid being locked into a proprietary system from the cloud provider, but also must ensure that service is compatible with the services offered by the cloud provider. A local key management system resides on the actual servers using the keys, which does not provide optimal security or control over them. Both the terms internal key management service and client key management service are provided as distractors.
NEW QUESTION: 3
どのタイプの脆弱性スキャナーがターゲットシステムをプローブして情報を取得しますか？
A. Direct
B. Active
C. Intrusive
D. Passive
Answer: B
NEW QUESTION: 4
한 회사가 Amazon EC2에서 상용 Apache Hadoop 클러스터를 실행하고 있습니다. 이 클러스터는 Amazon S3에서 대용량 파일을 쿼리하는 데 매일 사용됩니다. Amazon S3의 데이터는 선별되었으며 추가 변환 단계가 필요하지 않습니다. 이 회사는 Amazon EC2에서 상용 비즈니스 인텔리전스 (BI) 도구를 사용하여 Hadoop 클러스터에 대한 쿼리를 실행하고 데이터를 시각화 합니다.
이 회사는 Hadoop 클러스터 및 BI 도구 관리와 관련된 오버 헤드 비용을 줄이거 나 없애려고합니다. 회사는 최소한의 노력으로 보다 비용 효율적인 솔루션으로 제거하려고 합니다. 시각화는 간단하며 몇 가지 기본 집계 단계만 수행하면 됩니다.
회사의 요구 사항을 충족하는 옵션은 무엇입니까?
A. 일시적인 Amazon EMR 클러스터를 매일 시작하고 Apache Hive 스크립트를 개발하여 Amazon S3의 파일을 분석합니다. 작업이 완료되면 Amazon EMR 클러스터를 종료합니다. Amazon QuickSight를 사용하여 Amazon EMR에 연결하고 시각화를 수행합니다.
B. Amazon Athena를 사용하여 Amazon S3에서 파일을 쿼리하고 분석하는 스크립트를 개발합니다. 그런 다음 Amazon QuickSight를 사용하여 Athena에 연결하고 시각화를 수행합니다.
C. Amazon EC2에서 실행되는 상업용 ETL (추출, 변환,로드) 도구를 사용하여 처리 할 데이터를 준비합니다. 그런 다음 Amazon EC2에서 실행되는 더 빠르고 저렴한 Bl 도구로 전환하여 Amazon S3의 데이터를 시각화합니다.
D. Amazon EC2에서 실행되는 MySQL 데이터베이스에서 호출 된 저장 프로 시저를 개발하여 EC2를 분석하여 Amazon S3의 파일을 분석합니다. 그런 다음 Amazon EC2에서 실행되는 빠른 인 메모리 BL 도구를 사용하여 데이터를 시각화합니다.
Answer: B
Explanation:
Explanation
https://docs.aws.amazon.com/quicksight/latest/user/create-a-data-set-athena.html
https://aws.amazon.com/athena/