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NEW QUESTION: 1
注：この質問は、同じシナリオを提示する一連の質問の一部です。シリーズの各質問には、独自のソリューションが含まれています。ソリューションが規定の目標を満たしているかどうかを判断します。
会社のデータエンジニアリングソリューションを開発します。
プロジェクトでは、Azureでのバッチデータ処理のためにMicrosoft Azureにリソースを展開する必要があります
HDInsight。バッチ処理は毎日実行され、以下を行う必要があります。
コストを最小限に抑える拡張
クラスターのパフォーマンスを監視する
クラスタを監視し、スケーリング方法を提案する情報を提供するツールを推奨する必要があります。
解決策：Azure PowerShellを使用してAzure HDInsightクラスターログをダウンロードします。
ソリューションは目標を達成していますか？
A. いいえ
B. はい
Answer: A
Explanation:
代わりに、Azure Log AnalyticsおよびHDInsightクラスター管理ソリューションを使用してクラスターを監視します。
参照：
https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-hadoop-oms-log-analytics-tutorial

NEW QUESTION: 2
Which cloud service category most commonly uses client-side key management systems?
A. Software as a Service
B. Desktop as a Service
C. Platform as a Service
D. Infrastructure as a Service
Answer: A
Explanation:
SaaS most commonly uses client-side key management. With this type of implementation, the software for doing key management is supplied by the cloud provider, but is hosted and run by the cloud customer.
This allows for full integration with the SaaS implementation, but also provides full control to the cloud customer. Although the cloud provider may offer software for performing key management to the cloud customers, with the Infrastructure, Platform, and Desktop as a Service categories, the customers would largely be responsible for their own options and implementations and would not be bound by the offerings from the cloud provider.

NEW QUESTION: 3
You need to ensure that phone-based poling data can be analyzed in the PollingData database.
How should you configure Azure Data Factory?
A. Use a tumbling schedule trigger
B. Use manual execution
C. Use an event-based trigger
D. Use a schedule trigger
Answer: D
Explanation:
Explanation
When creating a schedule trigger, you specify a schedule (start date, recurrence, end date etc.) for the trigger, and associate with a Data Factory pipeline.
Scenario:
All data migration processes must use Azure Data Factory
All data migrations must run automatically during non-business hours
References:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-schedule-trigger
Topic 1, Proseware Inc
Background
Proseware, Inc, develops and manages a product named Poll Taker. The product is used for delivering public opinion polling and analysis.
Polling data comes from a variety of sources, including online surveys, house-to-house interviews, and booths at public events.
Polling data
Polling data is stored in one of the two locations:
* An on-premises Microsoft SQL Server 2019 database named PollingData
* Azure Data Lake Gen 2
Data in Data Lake is queried by using PolyBase
Poll metadata
Each poll has associated metadata with information about the poll including the date and number of respondents. The data is stored as JSON.
Phone-based polling
Security
* Phone-based poll data must only be uploaded by authorized users from authorized devices
* Contractors must not have access to any polling data other than their own
* Access to polling data must set on a per-active directory user basis
Data migration and loading
* All data migration processes must use Azure Data Factory
* All data migrations must run automatically during non-business hours
* Data migrations must be reliable and retry when needed
Performance
After six months, raw polling data should be moved to a lower-cost storage solution.
Deployments
* All deployments must be performed by using Azure DevOps. Deployments must use templates used in multiple environments
* No credentials or secrets should be used during deployments
Reliability
All services and processes must be resilient to a regional Azure outage.
Monitoring
All Azure services must be monitored by using Azure Monitor. On-premises SQL Server performance must be monitored.