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Free DP-203 Exam Braindumps (page: 9)

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PDF with 397 Questions

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Storage account that contains 100 GB of files. The files contain rows of text and numerical values. 75% of the rows contain description data that has an average length of 1.1 MB.

You plan to copy the data from the storage account to an enterprise data warehouse in Azure Synapse Analytics. You need to prepare the files to ensure that the data copies quickly.
Solution: You convert the files to compressed delimited text files. Does this meet the goal?

  1. Yes
  2. No

Answer(s): A

Explanation:

All file formats have different performance characteristics. For the fastest load, use compressed delimited text files.


Reference:

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data



Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Storage account that contains 100 GB of files. The files contain rows of text and numerical values. 75% of the rows contain description data that has an average length of 1.1 MB.

You plan to copy the data from the storage account to an enterprise data warehouse in Azure Synapse Analytics. You need to prepare the files to ensure that the data copies quickly.
Solution: You copy the files to a table that has a columnstore index. Does this meet the goal?

  1. Yes
  2. No

Answer(s): B

Explanation:

Instead convert the files to compressed delimited text files.


Reference:

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data



Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Storage account that contains 100 GB of files. The files contain rows of text and numerical values. 75% of the rows containdescription data that has an average length of 1.1 MB.

You plan to copy the data from the storage account to an enterprise data warehouse in Azure Synapse Analytics. You need to prepare the files to ensure that the data copies quickly.
Solution: You modify the files to ensure that each row is more than 1 MB. Does this meet the goal?

  1. Yes
  2. No

Answer(s): B

Explanation:

Instead convert the files to compressed delimited text files.


Reference:

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data



You build a data warehouse in an Azure Synapse Analytics dedicated SQL pool.
Analysts write a complex SELECT query that contains multiple JOIN and CASE statements to transform data for use in inventory reports. The inventory reports will use the data and additional WHERE parameters depending on the report. The reports will be produced once daily.
You need to implement a solution to make the dataset available for the reports. The solution must minimize query times.
What should you implement?

  1. an ordered clustered columnstore index
  2. a materialized view
  3. result set caching
  4. a replicated table

Answer(s): B

Explanation:

Materialized views for dedicated SQL pools in Azure Synapse provide a low maintenance method for complex analytical queries to get fast performance without any query change.

Incorrect Answers:
C: One daily execution does not make use of result cache caching.
Note: When result set caching is enabled, dedicated SQL pool automatically caches query results in the user database for repetitive use. This allows subsequent query executions to get results directly from the persisted cache so recomputation is not needed. Result set caching improves query performance and reduces compute resource usage. In addition, queries using cached results set do not use any concurrency slots and thus do not count against existing concurrency limits.


Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/performance-tuningmaterialized- views
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/performance-tuning-result-setcaching






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