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NEW QUESTION: 1
政府計画部門のソリューションを設計する必要があります。
どのサービスを設計に含める必要がありますか？
A. Azure SQL Database and Elastic Queries
B. Azure SQL Database and Polybase
C. Azure SQL Data Warehouse and Polybase
D. Azure SQL Data Warehouse and Elastic Queries
Answer: C
Explanation:
PolyBase is a new feature in SQL Server 2016. It is used to query relational and non-relational databases (NoSQL) such as CSV files.
Scenario: Traffic data must be made available to the Government Planning Department for the purpose of modeling changes to the highway system. The traffic data will be used in conjunction with other data such as information about events such as sporting events, weather conditions, and population statistics. External data used during the modeling is stored in on-premises SQL Server 2016 databases and CSV files stored in an Azure Data Lake Storage Gen2 storage account.
Reference:
https://www.sqlshack.com/sql-server-2016-polybase-tutorial/
Topic 6, Litware Case
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 questions in 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 section 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 in 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.
Overview
Litware, Inc. owns and operates 300 convenience stores across the US. The company sells a variety of packaged foods and drinks, as well as a variety of prepared foods, such as sandwiches and pizzas.
Litware has a loyalty club whereby members can get daily discounts on specific items by providing their membership number at checkout.
Litware employs business analysts who prefer to analyze data by using Microsoft Power BI, and data scientists who prefer analyzing data in Azure Databricks notebooks.
Requirements. Business Goals
Litware wants to create a new analytics environment in Azure to meet the following requirements:
* See inventory levels across the stores. Data must be updated as close to real time as possible.
* Execute ad hoc analytical queries on historical data to identify whether the loyalty club discounts increase sales of the discounted products.
* Every four hours, notify store employees about how many prepared food items to produce based on historical demand from the sales data.
Requirements. Technical Requirements
Litware identifies the following technical requirements:
* Minimize the number of different Azure services needed to achieve the business goals
* Use platform as a service (PaaS) offerings whenever possible and avoid having to provision virtual machines that must be managed by Litware.
* Ensure that the analytical data store is accessible only to the company's on-premises network and Azure services.
* Use Azure Active Directory (Azure AD) authentication whenever possible.
* Use the principle of least privilege when designing security.
* Stage inventory data in Azure Data Lake Storage Gen2 before loading the data into the analytical data store. Litware wants to remove transient data from Data Lake Storage once the data is no longer in use. Files that have a modified date that is older than 14 days must be removed.
* Limit the business analysts' access to customer contact information, such as phone numbers, because this type of data is not analytically relevant.
* Ensure that you can quickly restore a copy of the analytical data store within one hour in the event of corruption or accidental deletion.
Requirements. Planned Environment
Litware plans to implement the following environment:
* The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure.
* Customer data, including name, contact information, and loyalty number, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Product data, including product ID, name, and category, comes from Salesforce and can be imported into Azure once every eight hours. Row modified dates are not trusted in the source table.
* Daily inventory data comes from a Microsoft SQL server located on a private network.
* Litware currently has 5 TB of historical sales data and 100 GB of customer data. The company expects approximately 100 GB of new data per month for the next year.
* Litware will build a custom application named FoodPrep to provide store employees with the calculation results of how many prepared food items to produce every four hours.
* Litware does not plan to implement Azure ExpressRoute or a VPN between the on-premises network and Azure.
NEW QUESTION: 2
Scenario
A customer with a fully virtualized environment has four ESX 4.1 servers in a cluster with a SAN solution for storage. Each ESX server is hosting 40 virtual machines and all virtual machines have the same local disk configurations:
Disk1 = 50 GB
Disk2 = 100 GB
Disk3 = 256 GB
In addition, the environment includes a NAS filer. The average time to fully backup all virtual machines on one ESX server using EMC DD Boost is three hours.
The customer is interested in implementing an EMC NetWorker solution with Data Domain as a backup device. The backup server, storage nodes, and proxies are SAN-attached.
Refer to Scenario .
When using VADP backups with EMC NetWorker, which transport mode is recommended for virtual machines with IDE virtual disks?
A. SAN
B. Hotadd
C. NBD
D. RDM
Answer: C
NEW QUESTION: 3
SGACLをグローバルに有効にするために使用されたコマンドはどれですか？
Answer:
Explanation:
CTS役割ベースの施行
NEW QUESTION: 4
病院の医療機器を追跡している会社は、既存のストレージソリューションをAWSクラウドに移行したいと考えています。同社はすべてのデバイスに、位置と使用状況の情報を収集するセンサーを装備しています。このセンサーデータは、大きなスパイクを伴う予測できないパターンで送信されます。データは、各病院のオンプレミスで実行されているMySQLデータベースに保存されます。同社は、クラウドストレージソリューションを使用量に応じて拡張できることを望んでいます。
同社の分析チームは、センサーデータを使用して、デバイスの種類と病院ごとの使用量を計算します。チームは、クラウドからデータをフェッチしている間、分析ツールをローカルで実行し続ける必要があります。チームはまた、可能な限り少ない変更で既存のJavaアプリケーションとSQLクエリを使用する必要があります。
ソリューションアーキテクトは、センサーデータの安全性を確保しながら、これらの要件をどのように満たす必要がありますか？
A. データをAmazonS3バケットに保存します。 AWSPrivateLinkを使用してAmazonAthenaを介してデータを提供し、転送中のデータを保護します。
B. Amazon AuroraServerlessデータベースにデータを保存します。 AWS Identity and Access Management（1AM）およびAWS Secrets Manager ARNで承認された1AMユーザーを使用して、Aurora DataAPIを介してデータを提供します。
C. Amazon AuroraServerlessデータベースにデータを保存します。ネットワークロードバランサー（NLB）を介してデータを提供します。 AWS SecretsManagerに保存されている認証情報でNLBを使用してユーザーを認証します。
D. データをAmazonS3バケットに保存します。データソースとしてS3バケットを使用してAWSIdentity and Access Management（1AM）で承認された1AMユーザーを使用して、AmazonQuickSightを介してデータを提供します。
Answer: B
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