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NEW QUESTION: 1
You have an on-premises network that you plan to connect to Azure by using a site-to-site VPN.
In Azure, you have an Azure virtual network named VNet1 that uses an address space of 10.0.0.0/16. VNet1 contains a subnet named Subnet1 that uses an address space of 10.0.0.0/24.
You need to create a site-to-site VPN to Azure.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE:More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Answer:
Explanation:

Explanation


NEW QUESTION: 2
You execute the command to recover your database:
Which statement is true?
A. It restores all data files from the specified times, and then applies the redo logs.
B. It restores all data files and control files from the most recent backup taken before the ''until time'', and then recovers up to the ''until time using any restored archive logs that are needed to complete the task.
C. It restores the control file and all files from the most backup, and then applies the redo logs to the ''until time.
D. It restores all data files, redo log files, and control files, and then applies the redo logs up to the specified time.
Answer: C

NEW QUESTION: 3
Which of the following statements about Logical Volume Management (LVM) is true? Each correct answer represents a complete solution. Choose all that apply.
A. It can stripe whole or parts of logical volumes across multiple PVs, in a fashion similar to R AID0.
B. It cannot suffer from internal fragmentation.
C. It can resize logical volumes (LV) online by concatenating extents onto them or truncating extents from them.
D. It can resize volume groups online by absorbing new physical volumes (PV) or ejecting existing ones.
Answer: A,C,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 the data partitioning strategy.
How should you partition the Fact.Order table?
A. Create 730 partitions.
B. Create 17,520 partitions.
C. Create 2,557 partitions.
D. Use a granularity of two days.
Answer: C
Explanation:
We create on partition for each day. 7 years times 365 days is 2,555. Make that 2,557 to provide for leap years.
From scenario: Partition the Fact.Order table and retain a total of seven years of data.
Maximize the performance during the data loading process for the Fact.Order partition.