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NEW QUESTION: 1
회사는 민감한 사용자 데이터를 Amazon S3에 저장할 계획입니다. Amazon S3로 전송하기 전에 데이터의 내부 보안 준수 요구 사항 데이터를 데이터로 암호화합니다.
솔루션 아키텍트는 이러한 요구 사항을 충족시키기 위해 무엇을 권장해야 합니까?
A. AWS Key Management Service (AWS KMS)에 저장된 키를 사용한 서버 측 암호화
B. 고객 제공 암호화 키를 사용한 서버 측 암호화
C. AWS Key Management Service (AWS KMS)에 저장된 마스터 키를 사용한 클라이언트 측 암호화
D. Amazon S3 관리 암호화 키를 사용한 클라이언트 측 암호화
Answer: B

NEW QUESTION: 2
Match each characteristic to the correct storage type.

Answer:
Explanation:

Reference:
https://www.excitingip.com/1358/jbod-just-a-bunch-of-disks/ https://www.enterprisestorageforum.com/storage-networking/nas-vs.-san-differences-and-use-cases.html

NEW QUESTION: 3
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、指定された目標を達成する可能性のある独自のソリューションが含まれています。一部の質問セットには複数の正しい解決策がある場合がありますが、他の質問セットには正しい解決策がない場合があります。
このセクションの質問に回答した後は、その質問に戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
履歴データに基づいて気象条件を予測するモデルを作成します。
データストアからデータを読み込み、処理されたデータを機械学習モデルのトレーニングスクリプトに渡すために、処理スクリプトを実行するパイプラインを作成する必要があります。
解決策：次のコードを実行します。

ソリューションは目標を達成していますか？
A. はい
B. いいえ
Answer: A
Explanation:
Explanation
The two steps are present: process_step and train_step
Note:
Data used in pipeline can be produced by one step and consumed in another step by providing a PipelineData object as an output of one step and an input of one or more subsequent steps.
PipelineData objects are also used when constructing Pipelines to describe step dependencies. To specify that a step requires the output of another step as input, use a PipelineData object in the constructor of both steps.
For example, the pipeline train step depends on the process_step_output output of the pipeline process step:
from azureml.pipeline.core import Pipeline, PipelineData
from azureml.pipeline.steps import PythonScriptStep
datastore = ws.get_default_datastore()
process_step_output = PipelineData("processed_data", datastore=datastore) process_step = PythonScriptStep(script_name="process.py", arguments=["--data_for_train", process_step_output], outputs=[process_step_output], compute_target=aml_compute, source_directory=process_directory) train_step = PythonScriptStep(script_name="train.py", arguments=["--data_for_train", process_step_output], inputs=[process_step_output], compute_target=aml_compute, source_directory=train_directory) pipeline = Pipeline(workspace=ws, steps=[process_step, train_step]) Reference:
https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipelinedata?view=azu

NEW QUESTION: 4
Which of the completed statements is NOT true? The WebUI can be used to manage user accounts and:
A. assign privileges to users.
B. add users to your Gaia system.
C. edit the home directory of the user.
D. assign user rights to their home directory in the Security Management Server
Answer: D
Explanation:
Users
Use the WebUI and CLI to manage user accounts. You can: