Microsoft 70-776 MCSA: Data Engineering with Azure Questions

Microsoft 70-776 exam is a required test for MCSA: Data Engineering with Azure certification. MCSA: Data Engineering with Azure is a technical professional who Azure Data Factory Azure Data Lake Analytics Azure Stream Analytics. To help you pass Microsoft 70-776 exam, latest Microsoft 70-776 exam questions are available for you.

Microsoft 70-776 MCSA Practice Questions

Question: 1
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 are monitoring user queries to a Microsoft Azure SQL data warehouse that has six compute
nodes.
You discover that compute node utilization is uneven. The rows_processed column from
sys.dm_pdw_workers shows a significant variation in the number of rows being moved among the
distributions for the same table for the same query.
You need to ensure that the load is distributed evenly across the compute nodes.
Solution: You add a clustered columnstore index.
Does this meet the goal?
A. Yes
B. No

Answer: B

Question: 2
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 are monitoring user queries to a Microsoft Azure SQL data warehouse that has six compute
nodes.
You discover that compute node utilization is uneven. The rows_processed column from
sys.dm_pdw_workers shows a significant variation in the number of rows being moved among the
distributions for the same table for the same query.
You need to ensure that the load is distributed evenly across the compute nodes.
Solution: You add a nonclustered columnstore index.
Does this meet the goal?
A. Yes
B. No

Answer: B

Question: 3
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 sections, you will NOT be able to return to it. As a result, these
questions will not appear in the review screen.
You are monitoring user queries to a Microsoft Azure SQL data warehouse that has six compute
nodes.
You discover that compute node utilization is uneven. The rows_processed column from
sys.dm_pdw_workers shows a significant variation in the number of rows being moved among the
distributions for the same table for the same query.
You need to ensure that the load is distributed evenly across the compute nodes.
Solution: You change the table to use a column that is not skewed for hash distribution.
Does this meet the goal?
A. Yes
B. No

Answer: A

Question: 4
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 a table named Table1 that contains 3 billion rows. Table1 contains data from the last 36
months.
At the end of every month, the oldest month of data is removed based on a column named
DateTime.
You need to minimize how long it takes to remove the oldest month of data.
Solution: You specify DateTime as the hash distribution column.
Does this meet the goal?
A. Yes
B. No

Answer: B

Question: 5
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 a table named Table1 that contains 3 billion rows. Table1 contains data from the last 36
months.
At the end of every month, the oldest month of data is removed based on a column named
DateTime.
You need to minimize how long it takes to remove the oldest month of data.
Solution: You implement a columnstore index on the DateTime column.
Does this meet the goal?
A. Yes
B. No
Answer: A

Question: 6
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 a table named Table1 that contains 3 billion rows. Table1 contains data from the last 36
months.
At the end of every month, the oldest month of data is removed based on a column named
DateTime.
You need to minimize how long it takes to remove the oldest month of data.
Solution: You implement round robin for table distribution.
Does this meet the goal?
A. Yes
B. No

Answer: B