HOTSPOT
Your company has a Microsoft SQL Server data warehouse instance. The human resources department assigns all employees a unique identifier. You plan to store this identifier in a new table named Employee.
You create a new dimension to store information about employees by running the following Transact-SQL statement:

You have not added data to the dimension yet. You need to modify the dimension to implement a new column named [EmployeeKey]. The new column must use unique values.
How should you complete the Transact-SQL statements? To answer, select the appropriate Transact-SQL segments in the answer area.
Hot Area:

HOTSPOT
You manage a data warehouse in a Microsoft SQL Server instance. Company employee information is imported from the human resources system to a table named Employee in the data warehouse instance. The
Employee table was created by running the query shown in the Employee Schema exhibit. (Click the Exhibit button.)

The personal identification number is stored in a column named EmployeeSSN. All values in the EmployeeSSN column must be unique.
When importing employee data, you receive the error message shown in the SQL Error exhibit. (Click theExhibit button.).

You determine that the Transact-SQL statement shown in the Data Load exhibit in the cause of the error. (Click the Exhibit button.)

You remove the constraint on the EmployeeSSN column. You need to ensure that values in the EmployeeSSN column are unique.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:

non-NULL values but accept multiple NULL values.

HOTSPOTYou manage an inventory system that has a table named Products. The Products table has several hundred columns.
You generate a report that relates two columns named ProductReference and ProductName from the Products table. The result is sorted by a column named QuantityInStock from largest to smallest.
You need to create an index that the report can use.
How should you complete the Transact-SQL statement? To answer, select the appropriate Transact-SQL segments in the answer area.
Hot Area:

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 the storage for the data warehouse.
What change should you make?

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?

DRAG DROP

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 tochange 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.
Select and Place:

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. table using the ALTER TABLE (Transact-SQL) statement with the SWITCH PARTITION argument with SPLIT RANGE.

DRAG DROP

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.
Select and Place:

performance during the data loading process for the Fact.Order partition.

DRAG DROP

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.
Select and Place:

contains copies of production data for a development environment. database, use the sys.sp_cdc_enable_db stored procedure. sys.sp_cdc_enable_db has no parameters. sys.sp_cdc_enable_table https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/sys-sp-cdc-enable-dbtransact-sql

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? package by using the Control Flow tab in SSIS Designer.

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? package by using the Control Flow tab in SSIS Designer.