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NEW QUESTION: 1
Was fordert die Financial Action Task Force (FATF) ihre Mitglieder und alle anderen Gerichtsbarkeiten auf, zu tun, wenn in einer Gerichtsbarkeit eine laxe Bekämpfung von Geldwäsche / Gegenfinanzierung von Terrorismuskontrollen festgestellt wird?
A. Verhängung von Wirtschaftssanktionen, bis die FATF etwas anderes mitteilt
B. Stellen Sie die Geschäftstätigkeit mit dieser Gerichtsbarkeit sofort ein
C. Wenden Sie Gegenmaßnahmen gegen diese Gerichtsbarkeit an
D. Betrachten Sie Kunden aus dieser Gerichtsbarkeit als hohes Risiko
Answer: C
NEW QUESTION: 2
AWSに不慣れな企業は、Basic Supportプランにあるいくつかのアカウントでサービス制限を使い果たしたと報告しています。同社は、今後これが起こらないようにしたいと考えています。
会社のアカウントのすべてのサービス制限を監視および管理するための最も効率的な方法は何ですか？
A. AWSサポートに連絡して、すべてのアカウントで積極的に上限を引き上げます。このようにして、顧客はサービス制限を引き上げるためだけにインフラストラクチャの作成と管理を避けます。
B. Amazon CloudWatchとAWS Lambdaを使用して、AWS Trusted Advisorを使用してすべてのリンクされたアカウント間の制限を定期的に計算します。制限がしきい値を超える場合は、通知にAmazon SNSを使用します。アカウントが最低でもAWSビジネスサポートプランを使用していることを確認してください。
C. Amazon CloudWatchとAWS Lambdaを使用して、AWS Trusted Advisorを使用してすべてのリンクされたアカウント間の制限を定期的に計算し、プログラムでしきい値を超えそうな制限を増やします。
D. Amazon CloudWatchとAWS Lambdaを使用して、AWS Trusted Advisorを使用してすべてのリンクされたアカウント間の制限を定期的に計算し、制限がしきい値を超えている場合はAmazon SNSを使用して通知を提供します。
Answer: D
NEW QUESTION: 3
在庫レベルは、前日の最終在庫から当日の売上を差し引いて計算する必要があります。
Litwareに店舗と製品ごとに現在の在庫レベルを迅速に計算する機能を提供する2つのオプションはどれですか？それぞれの正解は完全な解決策を提示します。
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。
A. Event Hubs AvroファイルをAzure Blobストレージに出力します。 Transact-SQLを使用して、Azure SQL Data WarehouseのPolyBaseを使用して在庫レベルを計算します。
B. Azure Stream Analyticsを使用してイベントハブの出力を消費し、ストアおよび製品ごとにデータを集計します。結果のデータをAzure SQL Data Warehouseに直接出力します。 Transact-SQLを使用して、在庫レベルを計算します。
C. Databricksを使用して、イベントハブの出力を使用します。 Databricksを使用して在庫レベルを計算し、データをAzure SQL Data Warehouseに出力します。
D. Azure Stream Analyticsを使用してイベントハブの出力を消費し、ストアおよび製品ごとにデータを集計します。結果のデータをDatabricksに出力します。 Databricksのインベントリレベルを計算し、データをAzure Blobストレージに出力します。
E. Event Hubs AvroファイルをAzure Blobストレージに出力します。 Azure Data Factoryのコピーアクティビティをトリガーして、10分ごとに実行し、データをAzure SQL Data Warehouseに読み込みます。 Transact-SQLを使用して、ストアおよび製品ごとにデータを集計します。
Answer: B,E
Explanation:
Explanation
A: Azure Stream Analytics is a fully managed service providing low-latency, highly available, scalable complex event processing over streaming data in the cloud. You can use your Azure SQL Data Warehouse database as an output sink for your Stream Analytics jobs.
E: Event Hubs Capture is the easiest way to get data into Azure. Using Azure Data Lake, Azure Data Factory, and Azure HDInsight, you can perform batch processing and other analytics using familiar tools and platforms of your choosing, at any scale you need.
Note: Event Hubs Capture creates files in Avro format.
Captured data is written in Apache Avro format: a compact, fast, binary format that provides rich data structures with inline schema. This format is widely used in the Hadoop ecosystem, Stream Analytics, and Azure Data Factory.
Scenario: 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.
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/sql-data-warehouse/sql-data-warehouse-integrate-azure-stream-analy
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-capture-overview