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NEW QUESTION: 1
グローバルな小売企業のデータプラットフォームを開発しています。会社は各地域の通常の勤務時間中に営業しています。分析データベースは、販売予測の構築に週に1回使用されます。
各地域は、独自のプライベート仮想ネットワークを維持しています。
販売予測の構築は非常にリソース集約型であり、20テラバイト（TB）以上のデータを生成します。
Microsoft Azure SQLデータベースをプロビジョニングする必要があります。
データベースのプロビジョニングは、パフォーマンスを最大化し、コストを最小化する必要があります
各地域の日次売上は、Azure SQL Databaseインスタンスに保存する必要があります
1日に1回、すべてのリージョンのデータを分析Azure SQL Databaseインスタンスにロードする必要があります
Azure SQLデータベースインスタンスをプロビジョニングする必要があります。
データベースインスタンスをどのようにプロビジョニングする必要がありますか？答えるには、適切なAzure SQL製品を正しいデータベースにドラッグします。各Azure SQL製品は、1回、複数回、またはまったく使用できません。コンテンツを表示するには、ペイン間で分割バーをドラッグするか、スクロールする必要がある場合があります。
注：それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: Azure SQL Database elastic pools
SQL Database elastic pools are a simple, cost-effective solution for managing and scaling multiple databases that have varying and unpredictable usage demands. The databases in an elastic pool are on a single Azure SQL Database server and share a set number of resources at a set price. Elastic pools in Azure SQL Database enable SaaS developers to optimize the price performance for a group of databases within a prescribed budget while delivering performance elasticity for each database.
Box 2: Azure SQL Database Hyperscale
A Hyperscale database is an Azure SQL database in the Hyperscale service tier that is backed by the Hyperscale scale-out storage technology. A Hyperscale database supports up to 100 TB of data and provides high throughput and performance, as well as rapid scaling to adapt to the workload requirements. Scaling is transparent to the application - connectivity, query processing, and so on, work like any other SQL database.

NEW QUESTION: 2
6ホストの小規模オフィスでIPアドレスを割り当てるときのベストプラクティスは何ですか？
A. 各ノードに静的にアドレスを割り当てます。
B. ローカルCDPプロトコルを使用してアドレスを割り当てます。
C. ブランチオフィスにあるDHCPサーバーを使用します。
D. 本社にあるDHCPサーバーを使用します。
Answer: A
Explanation:
運用と管理が簡単なため、動的プロトコルを使用するのではなく、システムの数を管理できる静的アドレス指定スキームを使用するのが最適です。

NEW QUESTION: 3
You are creating the following two stored procedures:
A natively-compiled stored procedure

An interpreted stored procedure that accesses both disk-based and memory-optimized tables

Both stored procedures run within transactions.
You need to ensure that cross-container transactions are possible.
Which setting or option should you use?
A. the SET MEMORY_OPTIMIZED_ELEVATE_TO_SNAPSHOT=ONoption for the database
B. the SERIALIZABLEtable hint on disk-based tables
C. the SET TRANSACTION_READ_COMMITTEDisolation level for the connection
D. the SET MEMORY_OPTIMIZED_ELEVATE_TO_SNAPSHOT=OFFoption for the database
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Provide a supported isolation level for the memory-optimized table using a table hint, such as WITH (SNAPSHOT). The need for the WITH (SNAPSHOT) hint can be avoided through the use of the database option MEMORY_OPTIMIZED_ELEVATE_TO_SNAPSHOT. When this option is set to ON, access to a memory-optimized table under a lower isolation level is automatically elevated to SNAPSHOT isolation.
Incorrect Answers:
B: Accessing memory optimized tables using the READ COMMITTED isolation level is supported only for autocommit transactions. It is not supported for explicit or implicit transactions.
References: https://docs.microsoft.com/en-us/sql/relational-databases/in-memory-oltp/transactions-with- memory-optimized-tables?view=sql-server-2017

NEW QUESTION: 4
A company is planning to deploy a new business analytics application that requires 10.000 hours of compute time each month. The compute resources can have flexible availability, but must be as cost-effective as possible. The company will also provide a reporting service to distribute analytics reports, which needs to run at all times How should the solutions architect design a solution that meets these requirements?
A. Deploy the reporting service as a container in Amazon ECS with AWS Fargate as the compute option. Deploy the analytics application on a Spot Fleet. Set the analytics application to use a custom metric with Amazon EC2 Auto Scaling applied to the Spot Fleet.
B. Deploy the reporting service as a container in Amazon ECS with AWS Fargate as the compute option. Deploy the analytics application on an On-Demand Instance and purchase a Reserved Instance with a 3-year term. Set the analytics application to use a custom metric with Amazon EC2 Auto Scaling applied to the On-Demand Instance.
C. Deploy the reporting service on an On-Demand Instance. Deploy the analytics application as a container in AWS Batch with AWS Fargate as the compute option Set the analytics application to use a custom metric with Service Auto Scaling.
D. Deploy the reporting service on a Spot Fleet. Deploy the analytics application as a container in Amazon ECS with AWS Fargate as the compute option Set the analytics application to use a custom metric with Service Auto Scaling.
Answer: A