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NEW QUESTION: 1
Unternehmen haben zu viele Schwachstellen, um sie zu beheben, und müssen sich auf die konzentrieren, die die höchsten Risiken darstellen.
Welche Frage soll dem Interessenten gestellt werden, um ein Gespräch zu diesem Thema zu beginnen?
A. Mögen Sie die Berichte, die Sie aus Ihrem aktuellen Vulnerability Assessment-Tool erhalten?
B. Verwenden Sie derzeit einen Schwachstellenscanner?
C. Können Sie mir den Serverraum zeigen, um die physischen Sicherheitsmaßnahmen zu sehen?
D. Wie werden derzeit Schwachstellen behoben, die am wahrscheinlichsten zuerst ausgenutzt werden?
Answer: B

NEW QUESTION: 2

Use the following login credentials as needed:
Azure Username: xxxxx
Azure Password: xxxxx
The following information is for technical support purposes only:
Lab Instance: 10277521
You plan to deploy an integration runtime named Runtime1 to an Azure virtual machine.
You need to create an Azure Data Factory V2, and then prepare the required Data Factory resources for App1.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
Step 1: Create an Azure Data Factory V2
1. Go to the Azure portal.
2. Select Create a resource on the left menu, select Analytics, and then select Data Factory.

4. On the New data factory page, enter a name.
5. For Subscription, select your Azure subscription in which you want to create the data factory.
6. For Resource Group, use one of the following steps:
Select Use existing, and select an existing resource group from the list.
Select Create new, and enter the name of a resource group.
7. For Version, select V2.
8. For Location, select the location for the data factory.
9. Select Create.
10. After the creation is complete, you see the Data Factory page.
Step 2: Setup of the Integration Runtime Runtime1
High-level steps for creating a linked self-hosted IR
1. In the self-hosted IR Runtime to be shared, click Connections and Grant permission to another Data Factory. .

2. Select the data factory you just created.

Note the resource ID of the self-hosted IR to be shared.

3. In the data factory to which the permissions were granted, create a new self-hosted IR (linked) and enter the resource ID.


References:
https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal
https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime#sharing-the-self-hoste

NEW QUESTION: 3
大規模な複数年にわたる産業プロジェクトのプロジェクトマネージャーは、さまざまな地理的領域からの多様な利害関係者とのプロジェクトを持っています。最近、プロジェクトマネージャーは、利害関係者の関与に関する問題に遭遇しました。プロジェクトマネージャーは、関与が計画された効果をもたらさない根本的な理由を判断するために、どの2つのツールを使用する必要がありますか。 （2つ選択してください）
A. 5つのなぜ
B. 発行ログ
C. コミュニケーション管理計画
D. 石川図
E. オープンスペースミーティング
Answer: A,D

NEW QUESTION: 4
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have a Microsoft SQL Server data warehouse instance that supports several client applications.
The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.
All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.
You have the following requirements:
* Implement table partitioning to improve the manageability of the data warehouse and to avoid the need to repopulate all transactional data each night. Use a partitioning strategy that is as granular as possible.
* Partition the Fact.Order table and retain a total of seven years of data.
* Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest month of data is archived and removed.
* Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date tables.
* Incrementally load all tables in the database and ensure that all incremental changes are processed.
* Maximize the performance during the data loading process for the Fact.Order partition.
* Ensure that historical data remains online and available for querying.
* Reduce ongoing storage costs while maintaining query performance for current data.
You are not permitted to make changes to the client applications.
You need to implement partitioning for the Fact.Ticket table.
Which three actions should you perform in sequence? To answer, drag the appropriate actions to the correct locations. Each action may be used once, more than once or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: More than one combination of answer choices is correct. You will receive credit for any of the correct combinations you select.

Answer:
Explanation:

Explanation

From scenario: - Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest month of data is archived and removed.
The detailed steps for the recurring partition maintenance tasks are:
References:
https://docs.microsoft.com/en-us/sql/relational-databases/tables/manage-retention-of-historical-data-in-system-ve