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NEW QUESTION: 1
Sie haben Aufbewahrungsrichtlinien in Microsoft 365, wie in der folgenden Tabelle gezeigt.
Policy1 ist wie in der Policy1-Ausstellung gezeigt konfiguriert. (Drücke den
Policy1
Policy1 ist wie in der Policy2-Ausstellung gezeigt konfiguriert. (Klicken Sie auf die Registerkarte Policy2.) Policy2
Wählen Sie für jede der folgenden Anweisungen Ja aus, wenn die Anweisung wahr ist. Andernfalls wählen Sie Nein.
HINWEIS: Jede richtige Auswahl ist einen Punkt wert.
Answer:
Explanation:
Explanation
* Retention wins over deletion. Suppose that one retention policy says to delete Exchange email after three years, but another retention policy says to retain Exchange email for five years and then delete it.
Any content that reaches three years old will be deleted and hidden from the users' view, but still retained in the Recoverable Items folder until the content reaches five years old, when it is permanently deleted.
* The longest retention period wins. If content is subject to multiple policies that retain content, it will be retained until the end of the longest retention period.
Box 1: No.
The file will be deleted and hidden from the users' view, but still retained in the Recoverable Items folder. An administrator would need to recover the file.
Box 2: Yes.
The file will be deleted and hidden from the users' view, but still retained in the Recoverable Items folder. An administrator will be able to recover the file.
Box 3: Yes.
2018 to 2023 is five years. Policy2 has a retention period of four years. However, Policy2 is configured to not delete the files after the four-year retention period.
Reference:
https://docs.microsoft.com/en-us/office365/securitycompliance/retention-policies#the-principles-of-retention-or-
NEW QUESTION: 2
機械学習モデルを作成しています。 null行を含むデータセットがあります。
Azure Machine Learning StudioのClean Missing Dataモジュールを使用して、データセット内のnullデータと欠落データを特定して解決する必要があります。
どのパラメーターを使用する必要がありますか？
A. 平均で置換
B. 列全体を削除します
C. ホットデッキ
D. 行全体を削除します
Answer: B
Explanation:
Remove entire row: Completely removes any row in the dataset that has one or more missing values. This is useful if the missing value can be considered randomly missing.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data
NEW QUESTION: 3
What is the best example of a coaching or mentoring opportunity?
A. Exposure to internal experts
B. Sabbatical
C. Participating in a major project
D. On-line self-directed training
Answer: A