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NEW QUESTION: 1
Refer to the exhibits.
Design Option1:

Design Option 2:

Design Option 3:

Design Option 4:

An architect is helping an organization with the Conceptual Design of an NSX-T Data Center solution.
The conceptual design includes these requirements, assumptions, constraints, and risks:
Critical applications must run across sites without changing IP address.
Business continuity and disaster recovery (BCDR) plans will leverage a second site running vSphere.
RTO/RPO must be reduced for recovery of applications on secondary site.
IT Teams require automation tools for configuration.
Which Conceptual Design would the architect recommend to the customer? (Choose the best answer.)
A. Design Option 1
B. Design Option 2
C. Design Option 4
D. Design Option 3
Answer: A

NEW QUESTION: 2
When deploying to a Docker swarm, which section of the docker-compose file defines configuration related to the deployment and running of services?
A. services
B. build
C. args
D. deploy
Answer: D
Explanation:
Version 3 only.
Specify configuration related to the deployment and running of services. This only takes effect when deploying to a swarm withdocker stack deploy, and is ignored by docker-compose up and docker-compose run.
Reference: https://docs.docker.com/compose/compose-file/#deploy

NEW QUESTION: 3
AccessibilityToHighway列の欠落データを置き換える必要があります。
Clean Missing Dataモジュールをどのように構成する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: Replace using MICE
Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method described in the statistical literature as "Multivariate Imputation using Chained Equations" or
"Multiple Imputation by Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally using the other variables in the data before filling in the missing values.
Scenario: The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values.
Box 2: Propagate
Cols with all missing values indicate if columns of all missing values should be preserved in the output.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data