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NEW QUESTION: 1
Windows Server 2016を実行するServer1とServer2という2つのサーバーがあります。これらのサーバーはワークグループに属しています。
Server1のセキュリティ設定を含むセキュリティテンプレートを作成し、そのテンプレートをServer2に適用する必要があります。 解決策は管理作業を最小限に抑える必要があります。
各サーバーにどのスナップインを使用する必要がありますか？ 回答するには、適切なスナップインを正しいサーバーにドラッグします。
各スナップインは、1回、複数回、またはまったく使用しないことができます。 コンテンツを表示するには、ペイン間の分割バーをドラッグするか、スクロールする必要があります。
注：それぞれ正しい選択は1ポイントの価値があります。

Answer:
Explanation:

Explanation

References: https://www.windows-server-2012-r2.com/security-templates.html

NEW QUESTION: 2
An engineer maps a volume to the Windows 2012 R2 server and scans for disks within the Windows Disk Management Console. The engineer sees multiple instances of the mapped volume. The operating system was recently installed on the server that is experiencing the problem. No additional features have been added.
Which three steps should the engineer take within Windows to fix the problem? (Choose three.)
A. make sure that the iSCSI Initiator service runs on the server
B. add the Storage Center specific hardware ID within Windows MPIO
C. choose the disk object with the lowest disk number and delete the rest
D. add the 'Multipath I/O' server Feature
E. reboot the server after making the correct configuration changes
Answer: A,B,D

NEW QUESTION: 3
Which feature is an IPv6 security feature that is supported in Cisco IOS devices?
A. Secure Neighbor Discovery
B. Secure Gratuitous ARP
C. Secure ARP
D. IPv6 Sendmail
Answer: A

NEW QUESTION: 4
You are designing a solution for a company. The solution will use model training for objective
classification.
You need to design the solution.
What should you recommend?
A. Power BI models
B. a Spark application that uses Spark MLib.
C. an Azure Cognitive Services application
D. a Spark Streaming job
E. interactive Spark queries
Answer: B
Explanation:
Explanation/Reference:
Explanation:
Spark in SQL Server big data cluster enables AI and machine learning.
You can use Apache Spark MLlib to create a machine learning application to do simple predictive analysis
on an open dataset.
MLlib is a core Spark library that provides many utilities useful for machine learning tasks, including utilities
that are suitable for:
Classification

Regression

Clustering

Topic modeling

Singular value decomposition (SVD) and principal component analysis (PCA)

Hypothesis testing and calculating sample statistics

References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-machine-learning-mllib-ipython
Testlet 1
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you
would like to complete each case. However, there may be additional case studies and sections on this
exam. You must manage your time to ensure that you are able to complete all questions included on this
exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in
the case study. Case studies might contain exhibits and other resources that provide more information
about the scenario that is described in the case study. Each question is independent of the other question
on this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers
and to make changes before you move to the next sections of the exam. After you begin a new section,
you cannot return to this section.
To start the case study
To display the first question on this case study, click the Next button. Use the buttons in the left pane to
explore the content of the case study before you answer the questions. Clicking these buttons displays
information such as business requirements, existing environment, and problem statements. If the case
study has an All Information tab, note that the information displayed is identical to the information
displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to
return to the question.
Background
Trey Research is a technology innovator. The company partners with regional transportation department
office to build solutions that improve traffic flow and safety.
The company is developing the following solutions:

Regional transportation departments installed traffic sensor systems on major highways across North
America. Sensors record the following information each time a vehicle passes in front of a sensor:
Time

Location in latitude and longitude

Speed in kilometers per second (kmps)

License plate number

Length of vehicle in meters

Sensors provide data by using the following structure:

Traffic sensors will occasionally capture an image of a vehicle for debugging purposes.
You must optimize performance of saving/storing vehicle images.
Traffic sensor data
Sensors must have permission only to add items to the SensorData collection.

Traffic data insertion rate must be maximized.

Once every three months all traffic sensor data must be analyzed to look for data patterns that indicate

sensor malfunctions.
Sensor data must be stored in a Cosmos DB named treydata in a collection named SensorData

The impact of vehicle images on sensor data throughout must be minimized.

Backtrack
This solution reports on all data related to a specific vehicle license plate. The report must use data from
the SensorData collection. Users must be able to filter vehicle data in the following ways:
vehicles on a specific road

vehicles driving above the speed limit

Planning Assistance
Data used for Planning Assistance must be stored in a sharded Azure SQL Database.
Data from the Sensor Data collection will automatically be loaded into the Planning Assistance database
once a week by using Azure Data Factory. You must be able to manually trigger the data load process.
Privacy and security policy
Azure Active Directory must be used for all services where it is available.

For privacy reasons, license plate number information must not be accessible in Planning Assistance.

Unauthorized usage of the Planning Assistance data must be detected as quickly as possible.

Unauthorized usage is determined by looking for an unusual pattern of usage.
Data must only be stored for seven years.

Performance and availability
The report for Backtrack must execute as quickly as possible.

The SLA for Planning Assistance is 70 percent, and multiday outages are permitted.

All data must be replicated to multiple geographic regions to prevent data loss.

You must maximize the performance of the Real Time Response system.

Financial requirements
Azure resource costs must be minimized where possible.