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             I m  p l e m   e n ting a Data Warehouse using SQL
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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 sections, you will NOT be able to return to it. As a result, these 
questions will not appear in the review screen. 
You have a Microsoft Azure SQL Data Warehouse instance that must be available six months a day for 
reporting. 
You need to pause the compute resources when the instance is not being used. 
Solution: You use SQL Server Configuration Manager. 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
To pause a SQL Data Warehouse database, use any of these individual methods. 
Pause compute with Azure portal 
Pause compute with PowerShell 
Pause compute with REST APIs 
References: 
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-
overview 
 
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 sections, you will NOT be able to return to it. As a result, these 
questions will not appear in the review screen. 
You have a Microsoft Azure SQL Data Warehouse instance that must be available six months a day for 
reporting. 
You need to pause the compute resources when the instance is not being used. 
Solution: You use the Azure portal. 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
 
Answer: A     
 
 
Explanation: 
To pause a SQL Data Warehouse database, use any of these individual methods. 
Pause compute with Azure portal 
Pause compute with PowerShell 
Pause compute with REST APIs 
Note: To pause a database: 
1. Open the Azure portal and open your database. Notice that the Status is Online. 
 
2. To suspend compute and memory resources, click Pause, and then a confirmation message appears. 
Click yes to confirm or no to cancel. 
References: 
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-
overview 
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-
portal#pause-compute-bk 
 
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 have a Microsoft Azure SQL Data Warehouse instance that must be available six months a day for 
reporting. 
You need to pause the compute resources when the instance is not being used. 
Solution: You use SQL Server Management Studio (SSMS). 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
To pause a SQL Data Warehouse database, use any of these individual methods. 
Pause compute with Azure portal 
Pause compute with PowerShell 
Pause compute with REST APIs 
References: 
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-
overview 
 
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 sections, you will NOT be able to return to it. As a result, these 
questions will not appear in the review screen. 
You have a data warehouse that stores information about products, sales, and orders for a 
manufacturing company. The instance contains a database that has two tables named 
SalesOrderHeader and SalesOrderDetail. SalesOrderHeader has 500,000 rows and SalesOrderDetail has 
3,000,000 rows. 
Users report performance degradation when they run the following stored procedure: 
 
You need to optimize performance. 
Solution: You run the following Transact-SQL statement: 
 
 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
100 out of 500,000 rows is a too small sample size. 
References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-
statistics 
 
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 sections, you will NOT be able to return to it. As a result, these 
questions will not appear in the review screen. 
You have a data warehouse that stores information about products, sales, and orders for a 
manufacturing company. The instance contains a database that has two tables named 
SalesOrderHeader and SalesOrderDetail. SalesOrderHeader has 500,000 rows and SalesOrderDetail has 
3,000,000 rows. 
Users report performance degradation when they run the following stored procedure: 
 
You need to optimize performance. 
Solution: You run the following Transact-SQL statement: 
 
 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
Microsoft recommend against specifying 0 PERCENT or 0 ROWS in a CREATE STATISTICS..WITH SAMPLE 
statement. When 0 PERCENT or ROWS is specified, the statistics object is created but does not contain 
statistics data. 
References: https://docs.microsoft.com/en-us/sql/t-sql/statements/create-statistics-transact-sql 
 
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 sections, you will NOT be able to return to it. As a result, these 
questions will not appear in the review screen. 
You have a data warehouse that stores information about products, sales, and orders for a 
manufacturing company. The instance contains a database that has two tables named 
SalesOrderHeader and SalesOrderDetail. SalesOrderHeader has 500,000 rows and SalesOrderDetail has 
3,000,000 rows. 
Users report performance degradation when they run the following stored procedure: 
 
You need to optimize performance. 
Solution: You run the following Transact-SQL statement: 
 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
 
Answer: A     
 
 
Explanation: 
You can specify the sample size as a percent. A 5% statistics sample size would be helpful. 
References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-
statistics 
 
Question: 7 
   
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 have the following line-of-business solutions: 
ERP system 
Online WebStore 
Partner extranet 
One or more Microsoft SQL Server instances support each solution. Each solution has its own product 
catalog. You have an additional server that hosts SQL Server Integration Services (SSIS) and a data 
warehouse. You populate the data warehouse with data from each of the line-of-business solutions. The 
data warehouse does not store primary key values from the individual source tables. 
The database for each solution has a table named Products that stored product information. The 
Products table in each database uses a separate and unique key for product records. Each table shares a 
column named ReferenceNr between the databases. This column is used to create queries that involve 
more than once solution. 
You need to load data from the individual solutions into the data warehouse nightly. The following 
requirements must be met: 
If a change is made to the ReferenceNr column in any of the sources, set the value of IsDisabled to True 
and create a new row in the Products table. 
If a row is deleted in any of the sources, set the value of IsDisabled to True in the data warehouse. 
Solution: Perform the following actions: 
Enable the Change Tracking for the Product table in the source databases. 
Query the CHANGETABLE function from the sources for the updated rows. 
Set the IsDisabled column to True for the listed rows that have the old ReferenceNr value. 
Create a new row in the data warehouse Products table with the new ReferenceNr value. 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
 
Explanation: 
We must check for deleted rows, not just updates rows. 
References: https://www.timmitchell.net/post/2016/01/18/getting-started-with-change-tracking-in-sql-
server/ 
 
Question: 8 
   
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 have the following line-of-business solutions: 
ERP system 
Online WebStore 
Partner extranet 
One or more Microsoft SQL Server instances support each solution. Each solution has its own product 
catalog. You have an additional server that hosts SQL Server Integration Services (SSIS) and a data 
warehouse. You populate the data warehouse with data from each of the line-of-business solutions. The 
data warehouse does not store primary key values from the individual source tables. 
The database for each solution has a table named Products that stored product information. The 
Products table in each database uses a separate and unique key for product records. Each table shares a 
column named ReferenceNr between the databases. This column is used to create queries that involve 
more than once solution. 
You need to load data from the individual solutions into the data warehouse nightly. The following 
requirements must be met: 
If a change is made to the ReferenceNr column in any of the sources, set the value of IsDisabled to True 
and create a new row in the Products table. 
If a row is deleted in any of the sources, set the value of IsDisabled to True in the data warehouse. 
Solution: Perform the following actions: 
Enable the Change Tracking feature for the Products table in the three source databases. 
Query the CHANGETABLE function from the sources for the deleted rows. 
Set the IsDIsabled column to True on the data warehouse Products table for the listed rows. 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
We must check for updated rows, not just deleted rows. 
References: https://www.timmitchell.net/post/2016/01/18/getting-started-with-change-tracking-in-sql-
server/ 
 
 
Question: 9 
   
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 have the following line-of-business solutions: 
If a change is made to the ReferenceNr column in any of the sources, set the value of IsDisabled to True 
and create a new row in the Products table. 
If a row is deleted in any of the sources, set the value of IsDisabled to True in the data warehouse. 
One or more Microsoft SQL Server instances support each solution. Each solution has its own product 
catalog. You have an additional server that hosts SQL Server Integration Services (SSIS) and a data 
warehouse. You populate the data warehouse with data from each of the line-of-business solutions. The 
data warehouse does not store primary key values from the individual source tables. 
The database for each solution has a table named Products that stored product information. The 
Products table in each database uses a separate and unique key for product records. Each table shares a 
column named ReferenceNr between the databases. This column is used to create queries that involve 
more than once solution. 
You need to load data from the individual solutions into the data warehouse nightly. The following 
requirements must be met: 
Enable the Change Tracking for the Product table in the source databases. 
Query the cdc.fn_cdc_get_all_changes_capture_dbo_products function from the sources for updated 
rows. 
Set the IsDisabled column to True for rows with the old ReferenceNr value. 
Create a new row in the data warehouse Products table with the new ReferenceNr value. 
Solution: Perform the following actions: 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
We must also handle the deleted rows, not just the updated rows. 
References: https://solutioncenter.apexsql.com/enable-use-sql-server-change-data-capture/ 
 
Question: 10 
   
 
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 developing a Microsoft SQL Server Integration Services (SSIS) projects. The project consists of 
several packages that load data warehouse tables. 
You need to extend the control flow design for each package to use the following control flow while 
minimizing development efforts and maintenance: 
 
Solution: You add the control flow to a script task. You add an instance of the script task to the storage 
account in Microsoft Azure. 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
A package consists of a control flow and, optionally, one or more data flows. You create the control flow 
in a package by using the Control Flow tab in SSIS Designer. 
References: https://docs.microsoft.com/en-us/sql/integration-services/control-flow/control-flow 
 
 
Question: 11 
   
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 developing a Microsoft SQL Server Integration Services (SSIS) projects. The project consists of 
several packages that load data warehouse tables. 
You need to extend the control flow design for each package to use the following control flow while 
minimizing development efforts and maintenance: 
 
Solution: You add the control flow to an ASP.NET assembly. You add a script task that references this 
assembly to each data warehouse load package. 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: B     
 
 
Explanation: 
A package consists of a control flow and, optionally, one or more data flows. You create the control flow 
in a package by using the Control Flow tab in SSIS Designer. 
 
References: https://docs.microsoft.com/en-us/sql/integration-services/control-flow/control-flow 
 
Question: 12 
   
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 developing a Microsoft SQL Server Integration Services (SSIS) projects. The project consists of 
several packages that load data warehouse tables. 
You need to extend the control flow design for each package to use the following control flow while 
minimizing development efforts and maintenance: 
 
Solution: You add the control flow to a control flow package part. You add an instance of the control 
flow package part to each data warehouse load package. 
Does the solution meet the goal? 
 
A. Yes 
B. No 
 
Answer: A     
 
 
Explanation: 
 
A package consists of a control flow and, optionally, one or more data flows. You create the control flow 
in a package by using the Control Flow tab in SSIS Designer. 
References: https://docs.microsoft.com/en-us/sql/integration-services/control-flow/control-flow 
 
Question: 13 
   
DRAG DROP 
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: 
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-versioned-temporal-tables 
 
Question: 14 
   
 
DRAG DROP 
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 configure the Fact.Order table. 
Which three 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. 
 
 
 
Answer:  
 
 
 
Explanation: 
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. 
Step 1: Create a partition function. 
Using CREATE PARTITION FUNCTION is the first step in creating a partitioned table or index. 
 
Step 2: Create a partition scheme based on the partition function. 
To migrate SQL Server partition definitions to SQL Data Warehouse simply: 
Step 3: Execute an ALTER TABLE command to specify the partition function. 
References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-
partition 
 
Question: 15 
   
DRAG DROP 
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 optimize data loading for the Dimension.Customer table. 
Which three Transact-SQL segments should you use to develop the solution? To answer, move the 
appropriate Transact-SQL segments from the list of Transact-SQL segments to the answer area and 
arrange them in the correct order. 
NOTE: You will not need all of the Transact-SQL segments. 
 
 
 
Answer:  
 
 
 
Explanation: 
Step 1: USE DB1 
From Scenario: 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. 
 
Step 2: EXEC sys.sp_cdc_enable_db 
Before you can enable a table for change data capture, the database must be enabled. To enable the 
database, use the sys.sp_cdc_enable_db stored procedure. 
sys.sp_cdc_enable_db has no parameters. 
Step 3: EXEC sys.sp_cdc_enable_table 
@source schema = N 'schema' etc. 
Sys.sp_cdc_enable_table enables change data capture for the specified source table in the current 
database. 
Partial syntax: 
sys.sp_cdc_enable_table 
[ @source_schema = ] 'source_schema', 
[ @source_name = ] 'source_name' , [,[ @capture_instance = ] 'capture_instance' ] 
[,[ @supports_net_changes = ] supports_net_changes ] 
Etc. 
References: https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/sys-
sp-cdc-enable-table-transact-sql 
https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/sys-sp-cdc-
enable-db-transact-sql 
 
Question: 16 
   
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 17,520 partitions. 
B. Use a granularity of two days. 
C. Create 2,557 partitions. 
D. Create 730 partitions. 
 
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. 
 
Question: 17 
   
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: 
You are not permitted to make changes to the client applications. 
You need to optimize the storage for the data warehouse. 
What change should you make? 
 
A. Partition the Fact.Order table, and move historical data to new filegroups on lower-cost storage. 
B. Create new tables on lower-cost storage, move the historical data to the new tables, and then shrink 
the database. 
C. Remove the historical data from the database to leave available space for new data. 
D. Move historical data to new tables on lower-cost storage. 
 
 
Answer: A     
 
 
Explanation: 
Create the load staging table in the same filegroup as the partition you are loading. 
Create the unload staging table in the same filegroup as the partition you are deleteing. 
From scenario: Data older than one year is accessed infrequently and is considered historical. 
References: https://blogs.msdn.microsoft.com/sqlcat/2013/09/16/top-10-best-practices-for-building-a-
large-scale-relational-data-warehouse/