Free Microsoft DP-300 Exam Braindumps (page: 3)

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HOTSPOT (Drag and Drop is not supported)
You need to design an analytical storage solution for the transactional data. The solution must meet the sales transaction dataset requirements.

What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: Hash Scenario:
Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.

A hash distributed table can deliver the highest query performance for joins and aggregations on large tables. Box 2: Round-robin

Scenario:
You plan to create a promotional table that will contain a promotion ID. The promotion ID will be associated to a specific product. The product will be identified by a product ID. The table will be approximately 5 GB.

A round-robin table is the most straightforward table to create and delivers fast performance when used as a staging table for loads. These are some scenarios where you should choose Round robin distribution:
When you cannot identify a single key to distribute your data. If your data doesn’t frequently join with data from other tables. When there are no obvious keys to join.

Incorrect Answers:
Replicated: Replicated tables eliminate the need to transfer data across compute nodes by replicating a full copy of the data of the specified table to each compute node. The best candidates for replicated tables are tables with sizes less than 2 GB compressed and small dimension tables.


Reference:

https://rajanieshkaushikk.com/2020/09/09/how-to-choose-right-data-distribution-strategy-for-azure-synapse/



You have 20 Azure SQL databases provisioned by using the vCore purchasing model. You plan to create an Azure SQL Database elastic pool and add the 20 databases.
Which three metrics should you use to size the elastic pool to meet the demands of your workload? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

  1. total size of all the databases
  2. geo-replication support
  3. number of concurrently peaking databases * peak CPU utilization per database
  4. maximum number of concurrent sessions for all the databases
  5. total number of databases * average CPU utilization per database

Answer(s): A,C,E

Explanation:

CE: Estimate the vCores needed for the pool as follows:
For vCore-based purchasing model: MAX(<Total number of DBs X average vCore utilization per DB>,
<Number of concurrently peaking DBs X Peak vCore utilization per DB)

A: Estimate the storage space needed for the pool by adding the number of bytes needed for all the databases in the pool.


Reference:

https://docs.microsoft.com/en-us/azure/azure-sql/database/elastic-pool-overview



DRAG DROP (Drag and Drop is not supported)
You have SQL Server 2019 on an Azure virtual machine that contains an SSISDB database. A recent failure causes the master database to be lost.
You discover that all Microsoft SQL Server integration Services (SSIS) packages fail to run on the virtual machine.

Which four actions should you perform in sequence to resolve the issue? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Step 1: Attach the SSISDB database

Step 2: Turn on the TRUSTWORTHY property and the CLR property
If you are restoring the SSISDB database to an SQL Server instance where the SSISDB catalog was never created, enable common language runtime (clr)

Step 3: Open the master key for the SSISDB database
Restore the master key by this method if you have the original password that was used to create SSISDB.

open master key decryption by password = 'LS1Setup!' --'Password used when creating SSISDB' Alter Master Key Add encryption by Service Master Key
Step 4: Encrypt a copy of the mater key by using the service master key


Reference:

https://docs.microsoft.com/en-us/sql/integration-services/backup-restore-and-move-the-ssis-catalog



You have an Azure SQL database that contains a table named factSales. FactSales contains the columns shown in the following table.


FactSales has 6 billion rows and is loaded nightly by using a batch process.
Which type of compression provides the greatest space reduction for the database?

  1. page compression
  2. row compression
  3. columnstore compression
  4. columnstore archival compression

Answer(s): D

Explanation:

Columnstore tables and indexes are always stored with columnstore compression. You can further reduce the size of columnstore data by configuring an additional compression called archival compression.

Note: Columnstore — The columnstore index is also logically organized as a table with rows and columns, but the data is physically stored in a column-wise data format.

Incorrect Answers:
B: Rowstore — The rowstore index is the traditional style that has been around since the initial release of SQL Server.
For rowstore tables and indexes, use the data compression feature to help reduce the size of the database.


Reference:

https://docs.microsoft.com/en-us/sql/relational-databases/data-compression/data-compression



You have a Microsoft SQL Server 2019 database named DB1 that uses the following database-level and instance-level features.

-Clustered columnstore indexes
-Automatic tuning
-Change tracking
-PolyBase

You plan to migrate DB1 to an Azure SQL database.
What feature should be removed or replaced before DB1 can be migrated?

  1. Clustered columnstore indexes
  2. PolyBase
  3. Change tracking
  4. Automatic tuning

Answer(s): B

Explanation:

This table lists the key features for PolyBase and the products in which they're available.


Incorrect Answers:
C: Change tracking is a lightweight solution that provides an efficient change tracking mechanism for applications. It applies to both Azure SQL Database and SQL Server.

D: Azure SQL Database and Azure SQL Managed Instance automatic tuning provides peak performance and stable workloads through continuous performance tuning based on AI and machine learning.


Reference:

https://docs.microsoft.com/en-us/sql/relational-databases/polybase/polybase-versioned-feature-summary






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