70-767

70-767 practice questions, page 4 of 6, with answer review and explanations.

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 to 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?

  1. Create 17,520 partitions.
  2. Use a granularity of two days.
  3. Create 2,557 partitions.
  4. Create 730 partitions.

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 to 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?

  1. Partition the Fact.Order table, and move historical data to new filegroups on lower-cost storage.
  2. Create new tables on lower-cost storage, move the historical data to the new tables, and then shrink the database.
  3. Remove the historical data from the database to leave available space for new data.
  4. Move historical data to new tables on lower-cost storage.
  5. Implement row compression for the Fact.Order table.
  6. Move the index for the Fact.Order table to lower-cost storage.

Question 18

You 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:

Question 19

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 the Exhibit button.). You determine that the Transact-SQL statement shown in the Data Load exhibit is 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:

Question 20

You have a data warehouse. You need to move a table named Fact.ErrorLog to a new filegroup named LowCost. 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: