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NEW QUESTION: 1
A project manager is trying to ensure the quality of the design and reduce the number of potential defects. The project manager would like to use the fishbone diagram to perform this analysis. This type of modeling relies on:
A. Prioritizing the specific event.
B. Variance in the process over time.
C. Causes of a specific event.
D. Determining the number of events.
Answer: C

NEW QUESTION: 2
Your-company.com recently bought 2500 Chrome devices and wants to distribute them to various teams globally. You decided that enterprise enrollment would be the best way to enforce company policies for managed Chrome devices. You discovered that Chrome devices currently end up in the top-level organization unit, and this needs to change to the organizational unit of the device administrator.
What should you do?
A. Change Enrolment Permissions to not allow users in this organization to enroll new devices.
B. Change Enrollment Permissions to only allow users in this organization to re-enroll existing devices.
C. Change Enrollment Controls to Place Chrome device in user organization.
D. Change Enrollment Controls to Keep Chrome device in current location.
Answer: B

NEW QUESTION: 3
회사는 소규모 데이터 레코드 (최대 1KB)를 비용 효율적으로 최대 30 일 동안 유지해야 합니다. 데이터는 거의 읽지 않습니다. 데이터를 읽을 때 5 분 지연이 허용됩니다.
다음 중이 목표를 달성하는 솔루션은 무엇입니까? (두 가지를 선택하십시오.)
A. 레코드를 Amazon Kinesis Data Firehose에 기록하고 Kinesis Data Firehose를 구성하여 5 분 후에 Amazon S3에 데이터를 전달합니다. S3 버킷에서 30 일 만료 조치를 설정하십시오.
B. Redis를 위해 Amazon ElastiCache에 레코드를 작성하십시오. Amazon S3에 쓰기 위해 Redis 추가 전용 파일 (AOF) 지속성 로그를 구성하십시오. ElastiCache 인스턴스가 실패한 경우 로그에서 복구하십시오.
C. Amazon API 게이트웨이를 통해 호출 된 AWS Lambda 함수를 사용하여 5 분 동안 데이터를 수집합니다. 람다 실행이 중지되기 바로 전에 Amazon S3에 데이터를 작성하십시오.
D. Amazon S3를 사용하여 하나의 S3 객체에 여러 레코드를 수집합니다. 쓰기 직후 라이프 사이클 구성을 사용하여 Amazon Glacier로 데이터를 이동하십시오. 데이터를 읽을 때 신속한 검색을 사용하십시오.
E. TTL (Time To Live)이 30 일인 Amazon DynamoDB에 레코드를 작성하십시오. GetItem 또는 BatchGetItem 호출을 사용하여 데이터를 읽습니다.
Answer: C,E

NEW QUESTION: 4
ある会社が、Amazon S3の外部プロバイダーから送られてくるデータセットを受け取ります。異なるプロバイダからのデータセットは互いに依存しています。データセットは異なる時間に到着し、特定の順序はありません。
データアーキテクトは、会社が次のことを行えるようにするソリューションを設計する必要があります。
データが発生したらすぐにクロスデータセット分析を実行
*あり
異なる時間に到着するデータセット間の依存関係を管理する
*これらの要件を満たすスケーラブルで費用対効果の高いソリューションを提供するアーキテクチャ戦略はどれですか。
A. Amazon ElastiCache Redisクラスターのデータ依存情報を維持します。 Amazon S3イベント通知を使用して、S3オブジェクトをRedisにマッピングするAWS Lambda関数をトリガーします。タスクの依存関係が解決されたら、Amazon EMRでデータを処理します。
B. MySQL用Amazon RDSのデータ依存関係情報を管理します。 AWS Data Pipelineジョブを使用して、Amazon S3のタスク依存関係とイベント通知トリガーに基づいてAmazon EMR Hiveテーブルをロードします。
C. Amazon DynamoDBテーブルのデータ依存関係情報を管理します。 Amazon SNSおよびイベント通知を使用して、大量のAmazon EC2ワーカーにデータを公開します。タスクの依存関係が解決されたら、Amazon EMRでデータを処理します。
D. Amazon DynamoDBテーブルのデータ依存関係情報を管理します。 Amazon S3イベント通知を使用して、S3オブジェクトをDynamoDBで関連付けられているタスクにマッピングするAWS Lambda関数をトリガーします。すべてのタスク依存関係が解決されたら、Amazon EMRでデータを処理します。
Answer: A