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NEW QUESTION: 1
Your network contains an Active Directory domain named contoso.com.
The domain contains servers named Server1 and Server2 that run Windows Server 2012 R2.
Server1 has the IP Address Management (IPAM) Server feature installed.
You install the IPAM client on Server2.
You open Server Manager on Server2 as shown in the exhibit. (Click the Exhibit button.)

You need to manage IPAM from Server2.
What should you do first?
A. On Server1, add the Server2 computer account to the IPAM ASM Administrators group.
B. On Server2, add Server1 to Server Manager.
C. On Server1, add the Server2 computer account to the IPAM MSM Administrators group
D. On Server2, open Computer Management and connect to Server1.
Answer: B

NEW QUESTION: 2
In den späten 1980er Jahren prägte William Smith den Namen Six Sigma für eine Methodik, die ihren Ursprung in __________________ für dort geleistete qualitätsbezogene Arbeit hatte.
A. General Electric
B. Motorola
C. Honeywell
D. Alliiertes Signal
Answer: B

NEW QUESTION: 3
Server Intelligence Agentがサービスを制御できるホストはいくつですか。
A. ファイルリポジトリサーバーの数と同じ数
B. 処理サーバーの数と同じ数
C. 中央管理サーバーの数と同じ
D. 1つ
Answer: D

NEW QUESTION: 4
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に店舗および製品ごとの現在の在庫レベルをすばやく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：正しい選択はそれぞれ1ポイントの価値があります。
A. 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約します。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AzureBlobストレージに出力します。
B. Event HubsAvroファイルをAzureBlobストレージに出力します。 Transact-SQLを使用して、Azure SQL DataWarehouseのPolyBaseを使用して在庫レベルを計算します。
C. Event HubsAvroファイルをAzureBlob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 DataWarehouseに読み込みます。 Transact-SQLを使用して
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約します。結果のデータをAzureSQL DataWarehouse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。
E. Databricksを使用してイベントハブの出力を消費します。 Databricksを使用してインベントリレベルを計算し、データをAzureSQLデータウェアハウスに出力します。
Answer: C,D
Explanation:
data by store and product.
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-analytics
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-capture-overview

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