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NEW QUESTION: 1
Cisco APIC-EM ACLパスと一致するACEについて、どれが正しいですか。 （3つ選んでください。）
A. ACEは一致した場合にのみ報告されます。
B. トレースでACL内の一致するACEが見つからない場合は、暗黙的に許可されていると報告されます。
C. オプションの基準がトレースから省略されている場合、結果はデフォルト値が指定されているかのように報告されます。
D. オプションの基準がトレースから省略されている場合、結果にはすべての可能性のあるACEの一致が含まれます。
E. 一致しなかったものも含めて、トレースによって検出されたすべてのACEが報告されます。
F. トレースがACL内で一致するACEを見つけられなかった場合、それは暗黙的に拒否されたと報告されます。
Answer: A,D,F
Explanation:
The following rules effect the ACL path trace results:
Only matching ACEs are reported.
If you leave out the protocol, source port, or destination port when defining a path trace, the results include ACE matches for all possible values for these fields.
If no matching ACEs exists in the ACL, the flow is reported to be implicitly denied Reference: https://www.cisco.com/c/en/us/td/docs/cloud-systems-management/application-policy- infrastructure-controller-enterprise-module/1-2-x/config-guide/b_apic-em_config_guide_v_1-2- x/b_apic-em_config_guide_v_1-2-x_chapter_01000.pdf page 24

NEW QUESTION: 2
Which of the following statements are true?
I. Retail Risk Based Pricing involves using borrower specific data to arrive at both credit adjudication and pricing decisions II. An integrated 'Risk Information Management Environment' includes two elements - people and processes III. A Logical Data Model (LDM) lays down the relationships between data elements that an organization stores IV. Reference Data and Metadata refer to the same thing
A. All of the above
B. II and IV
C. I, II and III
D. I and III
Answer: D
Explanation:
Explanation
Statement I is correct. Retail Risk Based Pricing (RRBP) involves the use of borrower specific data (such as FICO scores, average balances etc) to arrive at credit decisions. These 'retail' credit decisions may include decisions on whether to grant a line of credit, a mortgage, issue a credit card, or any of the various other retail activities a bank may be dealing with. At the same time, this data can also be used to price the product, in addition to providing a yes or no credit decision so that risky borrowers are charged more than less risky borrowers.
Statement II is not correct, because an integrated Risk Information Management Environment includes three elements - people, processes and technology (and not just people and processes).
Statement III is correct. An LDM is a blue print of an organization's data, and describes the relationships between the various data elements.
Statement IV is not correct because reference data and metadata are not the same thing. Reference data refers to relatively static data, such as customer name (while actual transactions may not be so static). Metadata refers to data about data, and is stored in a data dictionary.
Therefore Choice 'b' is the correct answer and the rest are incorrect.

NEW QUESTION: 3
사진 공유 및 출판 회사는 매일 10,000 ~ 150,000 개의 이미지를 받습니다. 회사는 서비스에 등록 된 여러 공급 업체 및 사용자로 부터 이미지를 받습니다. 이 회사는 AWS로 이전 중이며 Amazon Rekognition을 사용하여 데이터를 추가하여 기존 메타 데이터를 보강하려고 합니다.
다음은 추가 데이터의 예입니다.

클라우드 마이그레이션 프로그램의 일환으로 이 회사는 기존 이미지 데이터를 Amazon S3에 업로드하고 사용자에게 Amazon S3에 직접 이미지를 업로드 하도록 지시했습니다.
이러한 요구 사항을 지원하기 위해 Solutions Architect는 무엇을 해야 합니까?
A. Amazon Kinesis를 사용하여 S3 이벤트를 기반으로 데이터를 스트리밍합니다. Amazon EC2에서 실행되는 애플리케이션을 사용하여 이미지에서 메타 데이터를 추출합니다. 그런 다음 Amazon DynamoDB 및 Amazon CloudSearch에 데이터를 저장하고 인덱스를 생성합니다. CloudSearch가 지원하는 검색 기능이 있는 웹 프런트 엔드를 사용합니다.
B. S3 이벤트 알림을 기반으로 Amazon SQS 대기열을 시작합니다. 그런 다음 Amazon SQS가 메타 데이터 정보를 Amazon DynamoDB로 보내도록합니다. Amazon EC2에서 실행되는 애플리케이션은 API를 사용하여 Amazon Rekognition에서 데이터를 추출하고 DynamoDB 및 Amazon ES에 데이터를 추가합니다. 웹 프런트 엔드를 사용하여 Amazon ES에서 지원하는 검색 기능을 제공합니다.
C. S3 이벤트 알림을 기반으로 AWS Lambda를 트리거하여 Amazon Rekognition을 사용하여 추가 메타 데이터를 생성합니다. Amazon DynamoDB를 사용하여 메타 데이터를 저장하고 Amazon ES를 사용하여 인덱스를 생성합니다. 웹 프런트 엔드를 사용하여 Amazon ES에서 지원하는 검색 기능을 제공합니다.
D. S3 이벤트 알림을 기반으로 AWS Lambda를 트리거하여 Amazon Rekognition을 사용하여 추가 메타 데이터를 생성합니다. Amazon RDS MySQL 다중 AZ를 사용하여 메타 데이터 정보를 저장하고 Lambda를 사용하여 인덱스를 생성합니다. Lambda에서 지원하는 검색 기능이있는 웹 프런트 엔드를 사용합니다.
Answer: C
Explanation:
https://github.com/aws-samples/lambda-refarch-imagerecognition