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NEW QUESTION: 1
ネットワークには、contoso.comという名前のActive Directoryドメインが含まれています。 ドメインには、次の表に示すように構成されたサーバーが含まれています。
すべてのサーバーはWindows Server 2016を実行します。すべてのクライアントコンピューターはWindows 10を実行し、ドメインメンバーです。
すべてのラップトップは、BitLockerドライブ暗号化（BitLocker）を使用して保護されています。アプリケーションサーバーのコンピュータアカウントを含むOU1という名前の組織単位（OU）があります。
OU2という名前のOUには、マーケティング部門のコンピュータのコンピュータアカウントが含まれています。
GP1という名前のグループポリシーオブジェクト（GPO）はOU1にリンクされています。
GP2という名前のGPOはOU2にリンクされています。
すべてのコンピュータは、Server1から更新を受信します。
Update1という名前の更新ルールを作成します。
AppLockerの規則がマーケティング部門のコンピュータに適用されるようにする必要があります。 あなたは何をするべきか？
A. OU2のプロパティから、COM +パーティションを変更します。
B. GP2では、アプリケーションIDサービスのスタートアップタイプを設定します。
C. GP2では、アプリケーション管理サービスのスタートアップの種類を構成します。
D. OU2のプロパティから、セキュリティ設定を変更します。
Answer: B
Explanation:
Explanation
https://docs.microsoft.com/en-us/windows/device-security/applocker/configure-the-application-identity-service Because AppLocker uses this service "Application Identity" to verify the attributes of a file, you must configure it to start automatically in at least one Group Policyobject (GPO) that applies AppLocker rules.
NEW QUESTION: 2
You deploy a real-time inference service for a trained model.
The deployed model supports a business-critical application, and it is important to be able to monitor the data submitted to the web service and the predictions the data generates.
You need to implement a monitoring solution for the deployed model using minimal administrative effort.
What should you do?
A. View the explanations for the registered model in Azure ML studio.
B. Create an ML Flow tracking URI that references the endpoint, and view the data logged by ML Flow.
C. View the log files generated by the experiment used to train the model.
D. Enable Azure Application Insights for the service endpoint and view logged data in the Azure portal.
Answer: A
NEW QUESTION: 3
A company just hired a new analyst. The new resource does not have any previous experience with Adobe Analytics but does with a different free Analytics tool, which is also install on the website for remarketing proposes. When analyzing Bounce Rate in both of the tool, the sees a significant different between them.
What is a possible reason for this different considering the implementation do not have any issues?
A. In Adobe Analytics, Bounce rate is calculated using the formula ''Bounces divided by Entries ''. In some other Analytic tools. Bounce rate is calculated using the formula ''Single-page session divided by sessions.''
B. In Adobe Analyst Bounce rate is calculated using the formula ''Session divided by Enteries. In some other Analytics tools, Bounce rate is calculated using the formula Single session divided by session.
C. They way Adobe analytics visitors is different from the rest of the market based on IP addresses.
D. In Adobe Analytics calculate Visitors is different from the rest of the market based on IP addresses.
E. Metrics can never be compared between two different tools
Answer: A