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NEW QUESTION: 1
An administrator sees that an environment has a long startup time and wants to remedy the issue.
Which solution should be used?
A. Reduce the size of the Content Store through archiving and removal.
B. Check the Fast Startup option under IBM Cognos Configuration.
C. Increase the size of the JVM heap by selecting Large configuration.
D. Set load balancing to cluster compatible.
Answer: D
Explanation:
If your IBM Cognos servers operate within a load balancing infrastructure, you can turn off the weighted round robin format of load balancing for the dispatcher. Otherwise, load balancing may be duplicated by the cluster and by IBM Cognos software, which can degrade performance.
You can set the dispatcher property named loadBalancingMode either to
weightedRoundRobin or clusterCompatible.
References: IBM Cognos Administration Version 10.1.0, Administration and Security Guide, page 163
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.
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. encryption
B. anonymization
C. obfuscation
D. compression
Answer: C
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: 3
Adobe Analytics開発者は、AdobeAnalyticsで新しいeVarの分類ルールを作成する必要があります。開発者はルールビルダーツールを使用しており、最初のルールを新しいルールセットに追加しています。彼らはルールタイプと一致基準を開発しました。新しいeVarの分類は、正しいレポートスイートで使用可能な変数のリストに表示されません。
この問題の考えられる理由は何ですか？
A. 開発者は、ルールビルダーを使用してeVarの新しい分類を作成する必要があります。
B. 変数を表示するには、開発者はAdobeAnalyticsからログアウトして再度ログインする必要があります。
C. 開発者は、変数がリストに表示される前に、データが収集されるのを24〜48時間待つ必要があります。
D. 開発者は、ルールビルダーでルールセットを作成する前に、eVarの分類レポート名を作成する必要があります。
Answer: A