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Interior Design Professional Exam

  • Exam Number/Code : IDPX
  • Exam Name : Interior Design Professional Exam
  • Questions and Answers : 213 Q&As
  • Update Time: 2019-01-10
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NEW QUESTION: 1
Refer to the exhibit.

What is the purpose of eth2 on the CVMs?
A. iSCSI connectivity
B. Network Segmentation
C. Remote site connectivity
D. RDMA Network Segmentation
Answer: D
Explanation:
Explanation
Ref: https://next.nutanix.com/installation-configuration-23/backplane-network-in-aos-5-5-27291

NEW QUESTION: 2

A. Option A
B. Option D
C. Option B
D. Option C
Answer: C

NEW QUESTION: 3
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.
You need to recommend a data handling solution to support the planned changes to the dashboard.
What is the best recommendation to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.
A. obfuscation
B. compression
C. anonymization
D. encryption
Answer: A
Explanation:
Explanation/Reference:
Explanation:
From scenario: 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.
The developers must be prevented from accessing the private information of the users.
Dynamic Data Masking can be used to hide or obfuscate sensitive data, by controlling how the data appears in the output of database queries.
Dynamic Data Masking rules can be defined on particular columns, indicating how the data in those columns will appear when queried. There are no physical changes to the data in the database itself; the data remains intact and is fully available to authorized users or applications. Database operations remain unaffected, and the masked data has the same data type as the original data, so DDM can often be applied without making any changes to database procedures or application code.
Reference: https://blogs.technet.microsoft.com/dataplatforminsider/2016/01/25/use-dynamic-data- masking-to-obfuscate-your-sensitive-data/

NEW QUESTION: 4

Answer:
Explanation:
HISTFILE