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Exam Code: dbt-Analytics-Engineering Dumps

Questions and Answers: 104

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NEW QUESTION: 1
축구를 때려 박는 것은 행동의 평면에서 발생하는 엉덩이 굴곡을 필요로 합니까?
A. 가로
B. 이축
C. 정면
D. Sagittal
Answer: D

NEW QUESTION: 2
Subscription1이라는 Azure 구독이 있습니다.
Subscription1에서 share1이라는 Azure 파일 공유를 만듭니다.
다음 전시회에 표시된 것처럼 SAS1이라는 공유 액세스 서명 (SAS)을 작성합니다.

답변하려면 답변 영역에서 적절한 옵션을 선택하십시오.
참고 : 각각의 올바른 선택은 1 포인트의 가치가 있습니다.

Answer:
Explanation:

Explanation:
Box 1: Will be prompted for credentials
Azure Storage Explorer is a standalone app that enables you to easily work with Azure Storage data on Windows, macOS, and Linux. It is used for connecting to and managing your Azure storage accounts.
Box 2: Will have read, write, and list access
The net use command is used to connect to file shares.
References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-dotnet-shared-access-signature-part-1
https://docs.microsoft.com/en-us/azure/vs-azure-tools-storage-manage-with-storage-explorer?tabs=windows

NEW QUESTION: 3
Which of the following statements are true about a data mart?
Each correct answer represents a complete solution.
A. Most writers believe that the design of a data mart tends to start from an analysis of the data already existing.
B. Users of a data mart can expect to have data presented in terms that are familiar to them.
C. The emphasis of a data mart is on meeting the specific demands of a particular group of knowledge users.
D. A data mart is a repository of data gathered from operational data.
Answer: B,C,D
Explanation:
Explanation/Reference:
Explanation:
A data mart is a repository of data gathered from operational data and other sources that is designed to serve a particular community of knowledge workers. In scope, the data may derive from an enterprise-wide database or data warehouse or be more specialized. The emphasis of a data mart is on meeting the specific demands of a particular group of knowledge users in terms of analysis, content, presentation, and ease-of-use. Users of a data mart can expect to have data presented in terms that are familiar.
In practice, the terms data mart and data warehouse each tend to imply the presence of the other in some form. However, most writers using the term seem to agree that the design of a data mart tends to start from an analysis of user needs and that a data warehouse tends to start from an analysis of what data already exists and how it can be collected in such a way that the data can later be used. A data warehouse is a central aggregation of data (which can be distributed physically); a data mart is a data repository that may derive from a data warehouse or not and that emphasizes ease of access and usability for a particular designed purpose. In general, a data warehouse tends to be a strategic but somewhat unfinished concept; a data mart tends to be tactical and aimed at meeting an immediate need.
A is incorrect. Writers using a data mart believe that the design of a data mart tends to start from
an analysis of user needs.


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