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NEW QUESTION: 1
次の展示に示すように、仮想マシンを作成する予定です。

ドロップダウンメニューを使用して、図に示されている情報に基づいて各ステートメントを完成させる回答の選択肢を選択します。
注：各正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: is guaranteed to remain the same
OS disk type: Premium SSD
Premium SSD Managed Disks are high performance Solid State Drive (SSD) based Storage designed to support I/O intensive workloads with significantly high throughput and low latency. With Premium SSD Managed Disks, you can provision a persistent disk and configure its size and performance characteristics.
Box 2: secure enclaves
Virtual machine size: Standard_DC2s
DC-series virtual machines are a new family of VMs to protect the confidentiality and integrity of your data and code while it's processed in Azure through the use of secure enclaves.
Incorrect:
Not dm-crypt: Azure Disk Encryption helps protect and safeguard your data to meet your organizational security and compliance commitments. It uses the BitLocker feature of Windows and the DM-Crypt feature of Linux to provide volume encryption for the OS and data disks of Azure virtual machines (VMs).
References:
https://docs.microsoft.com/en-us/azure/virtual-machines/windows/disks-types
https://azure.microsoft.com/en-us/pricing/details/virtual-machines/series/

NEW QUESTION: 2
Overview:
Litware, Inc. is a company that manufactures personal devices to track physical activity and other health- related data.
Litware has a health tracking application that sends health-related data from a user's personal device to Microsoft Azure.
Litware has three development and commercial offices. The offices are located in the United States, Luxembourg, and India.
Litware products are sold worldwide. Litware has commercial representatives in more than 80 countries.
Existing Environment:
In addition to using desktop computers in all of the offices, Litware recently started using Microsoft Azure resources and services for both development and operations.
Litware has an Azure Machine Learning solution.
Litware recently extended its platform to provide third-party companies with the ability to upload data from devices to Azure. The data can be aggregated across multiple devices to provide users with a comprehensive view of their global health activity.
While the upload from each device is small, potentially more than 100 million devices will upload data daily by using an Azure event hub.
Each health activity has a small amount of data, such as activity type, start date/time, and end date/time.
Each activity is limited to a total of 3 KB and includes a customer identification key.
In addition to the Litware health tracking application, the users' activities can be reported to Azure by using an open API.
The developers at Litware perform Machine Learning experiments to recommend an appropriate health activity based on the past three activities of a user.
The Litware developers train a model to recommend the best activity for a user based on the hour of the day.
Requirements:
Litware plans to extend the existing dashboard features so that health activities can be compared between the users based on age, gender, and geographic region.
Minimize the costs associated with transferring data from the event hub to Azure Storage.
Litware identifies the following technical requirements:
Data from the devices must be stored for three years in a format that enables the fast processing of

date fields and filtering.
The third-party companies must be able to use the Litware Machine Learning models to generate

recommendations to their users by using a third-party application.
Any changes to the health tracking application must ensure that the Litware developers can run the

experiments without interrupting or degrading the performance of the production environment.
Activity tracking data must be available to all of the Litware developers for experimentation. The developers must be prevented from accessing the private information of the users.
When the Litware health tracking application asks users how they feel, their responses must be reported to Azure.
Users report that when they access data that is more than one year old from a dashboard, the response time is slow.
You need to resolve the issue that causes the slow response when visualizing older data.
What should you do?
A. Process the older data on demand first, and then process the event hub data.
B. Store all of the data from the event hub in a single partition.
C. Aggregate the older data by time, and then save the aggregated data to reference data streams.
D. Process the event hub data first, and then process the older data on demand.
Answer: C
Explanation:
Explanation/Reference:
Explanation:

NEW QUESTION: 3
Evaluate the following Python arithmetic expression:

What is the result?
A. 0
B. 1
C. 2
D. 3
Answer: C
Explanation:
Explanation/Reference:
References: http://www.mathcs.emory.edu/~valerie/courses/fall10/155/resources/op_precedence.html

NEW QUESTION: 4
Which of the following sectors on a hard disk contains codes that the computer uses to start the system?
A. Sector 1
B. Sector 0
C. Sector 256
D. Sector 128
Answer: B