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NEW QUESTION: 1
For which three objects can you configure the out-of-box "Restricted Party Screening" UI action in the Screen Set for performing Restricted Party Screening? (Choose three.)
A. Trade Transaction
B. Trade Transaction Line
C. Shipment
D. Party
E. Item
Answer: B,C,E

NEW QUESTION: 2
Tabie1という名前のテーブルを含むDB1という名前のデータベースがあります。 Table1には、index1という名前の非クラスタ化インデックスがあります。
index1が破損していることがわかります。
あなたはindex1を修復する必要があります。
どのステートメントを実行しますか？
A. drop index 1 on tabie 1
B. DBCC CHECKOB（ 'db1 *、TABLOCK）
C. table1のALTER INDEX index1がリビルドされました（ONLINE = 0N）
D. DBCC CHECKDB（* db1、REPAIR_FAST）
Answer: C
Explanation:
If REBUILD is performed online (ON) the data in this table is available for queries and data modification during the index operation.
References:
https://docs.microsoft.com/en-us/sql/t-sql/statements/alter-index-transact-sql?view=sql-server-2017
https://docs.microsoft.com/en-us/sql/t-sql/database-console-commands/dbcc-checkdb-transact-sql?view=sqlserver-
2017

NEW 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 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 data warehouse that stores sales data. One fact table has 100 million rows.
You must reduce storage needs for the data warehouse.
You need to implement a solution that uses column-based storage and provides real-time analytics for the operational workload.
Solution: You remove any clustered indexes and load the table for processing.
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Clustered columnstore tables offer both the highest level of data compression as well as the best overall query performance. Clustered columnstore tables will generally outperform clustered index or heap tables and are usually the best choice for large tables. For these reasons, clustered columnstore is the best place to start when you are unsure of how to index your table.
Note: Dimensional tables can be used to reduce the size of fact tables.
Dimension tables contain attribute data that might change but usually changes infrequently.
For example, a customer's name and address are stored in a dimension table and updated only when the customer's profile changes. To minimize the size of a large fact table, the customer's name and address do not need to be in every row of a fact table. Instead, the fact table and the dimension table can share a customer ID. A query can join the two tables to associate a customer's profile and transactions.
References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data- warehouse-tables-overview