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NEW QUESTION: 1
You are designing an extract, transform, load (ETL) process for loading data from a SQL Server database into a large fact table in a data warehouse each day with the prior day's sales data.
The ETL process for the fact table must meet the following requirements:
-----
Load new data in the shortest possible time.
Remove data that is more than 36 months old.
Ensure that data loads correctly.
Minimize record locking.
Minimize impact on the transaction log.
You need to design an ETL process that meets the requirements. What should you do? (More than one answer choice may achieve the goal. Select the BEST answer.)
A. Partition the destination fact table by date. Use partition switching and a staging table to remove old data. Insert new data directly into the fact table.
B. Partition the destination fact table by customer. Use partition switching both to remove old data and to load new data into each partition.
C. Partition the destination fact table by date. Insert new data directly into the fact table and delete old data directly from the fact table.
D. Partition the destination fact table by date. Use partition switching and staging tables both to remove old data and to load new data.
Answer: D

NEW QUESTION: 2
A DevOps Engineer is deploying a new web application. The company chooses AWS Elastic Beanstalk for deploying and managing the web application, and Amazon RDS MySQL to handle persistent data. The company requires that new deployments have minimal impact if they fail.
The application resources must be at full capacity during deployment, and rolling back a deployment must also be possible.
Which deployment sequence will meet these requirements?
A. Deploy the application using Elastic Beanstalk, and include RDS MySQL as part of the environment.
Use default Elastic Beanstalk behavior to deploy changes to the application, and let rolling updates deploy changes to the application.
B. Deploy the application using Elastic Beanstalk, and include RDS MySQL as part of the environment.
Use Elastic Beanstalk immutable updates for application deployments.
C. Deploy the application using Elastic Beanstalk and connect to an external RDS MySQL instance using Elastic Beanstalk environment properties. Use Elastic Beanstalk features for a blue/green deployment to deploy the new release to a separate environment, and then swap the CNAME in the two environments to redirect traffic to the new version.
D. Deploy the application using Elastic Beanstalk, and connect to an external RDS MySQL instance using Elastic Beanstalk environment properties. Use Elastic Beanstalk immutable updates for application deployments.
Answer: C
Explanation:
https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/AWSHowTo.RDS.html

NEW QUESTION: 3
한 컴퓨터에서 다른 컴퓨터로 데이터가 통신 될 때 오류를 감지하는데 도움이 되는 하드웨어 컨트롤은 다음과 같습니다.
A. 패리티 검사.
B. 테이블 조회.
C. 유효성 검사
D. 중복 검사.
Answer: A
Explanation:
설명:
패리티 검사는 메모리에서 데이터를 읽거나 한 컴퓨터에서 다른 컴퓨터로 통신 할 때 데이터 오류를 감지하는데 도움이 됩니다. 데이터 항목에 1 비트 숫자 (0 또는 1)가 추가되어 해당 데이터 항목의 비트 합계가 홀수인지 짝수인지 나타냅니다. 패리티 비트가 다른 비트의 합과 일치하지 않으면 오류 보고서가 생성됩니다.

NEW QUESTION: 4
Which best describes the benefit of unit testing rules? (Choose One)
A. Unit testing validates information that must be provided before the rule can be saved.
B. Unit testing validates a rule configuration to ensure that any dependent rules are available to the application.
C. Unit testing identifies configuration issues that can propagate to other rules with potentially serious consequences.
D. Unit testing identifies configuration issues that may impact application performance on a production system.
Answer: C