Adaface Sample SQL Server Questions

As a DBA, you receive an alert notifying you that the production database has gone offline due to a severe issue. Fortunately, you have a proper backup strategy in place. The backups are performed as follows:
            
            1. Full database backup every Sunday at 2:00 AM.
            2. Differential backup every day at 2:00 AM, except Sunday.
            3. Transaction log backup every hour.

Today is Wednesday, and the failure occurred at 10:15 AM. You have the following backup files available:
            
            1. Full backup: Full_Backup_Sun.bak taken on Sunday 2:00 AM.
            2. Differential backups: Diff_Backup_Mon.bak, Diff_Backup_Tue.bak, Diff_Backup_Wed.bak taken at 2:00 AM on their respective days.
            3. Transaction log backups: Hourly backups from Sunday 3:00 AM until Wednesday 10:00 AM, like TLog_Backup_Wed_09.bak, TLog_Backup_Wed_10.bak.

Given the RPO (Recovery Point Objective) of 15 minutes, which of the following sequences of restore operations would ensure minimal data loss?

A: Full_Backup_Sun.bak, Diff_Backup_Wed.bak, then all Transaction Log backups from Wednesday.
            
            B: Full_Backup_Sun.bak, Diff_Backup_Tue.bak, then all Transaction Log backups from Tuesday and Wednesday.
            
            C: Full_Backup_Sun.bak, Diff_Backup_Wed.bak, then Transaction Log backups from Wednesday 2:00 AM to 10:00 AM.
            
            D: Full_Backup_Sun.bak, then all Transaction Log backups from Sunday to Wednesday 10:00 AM.
            
            E: Full_Backup_Sun.bak, Diff_Backup_Mon.bak, Diff_Backup_Tue.bak, Diff_Backup_Wed.bak, then Transaction Log backups from Wednesday 2:00 AM to 10:00 AM.

You are managing a SQL Server database for a large e-commerce platform. The database contains the following tables:

Users often run a query to retrieve all orders from a specific date along with customer details and a breakdown of each order. Lately, this query has been performing poorly, especially on days with a high volume of orders.
            
            Given this schema, which of the following changes would MOST LIKELY enhance the performance of this query?

A: Create a non-clustered index on Orders(OrderDate, OrderID) and a clustered index on OrderDetails(OrderID).
            B: Create a clustered index on Orders(CustomerID, OrderDate) and a non-clustered index on OrderDetails(ProductName).
            C: Increase the size of the OrderDetails(ProductName) column and add more RAM to the SQL Server machine.
            D: Create a clustered index on Orders(OrderDate) and a non-clustered index on OrderDetails(OrderID, Quantity).
            E: Partition the Orders table on OrderDate and create a non-clustered index on OrderDetails(DetailID, Price).

You are managing a SQL Server instance that is experiencing performance degradation. After some analysis, you realize that the TempDB is under heavy stress due to numerous long-running transactions. Users have reported that some SELECT queries on a large table, named SalesData, are slower than expected.
            
            You consider implementing Snapshot Isolation to mitigate blocking issues. You're aware that Snapshot Isolation uses TempDB to store row versions.
            
            Given the situation, which combination of actions will help alleviate the stress on TempDB and enhance the performance of SELECT queries on SalesData?

A: Move TempDB to a faster storage subsystem and enable Snapshot Isolation for SalesData.
            B: Increase the number of TempDB data files, shrink TempDB size, and enable Snapshot Isolation for the database.
            C: Implement Read Committed Snapshot Isolation (RCSI) for the database and partition the SalesData table.
            D: Reduce the TempDB size, implement table partitioning on SalesData, and enable Read Uncommitted isolation level for the SELECT queries.
            E: Create a non-clustered index on frequently queried columns of SalesData and enable row versioning for the entire database.

You are a DBA at a large company managing an SQL Server database which is crucial for daily operations. The database is configured with the Full recovery model. The database is experiencing considerable transaction log growth during business hours, which is impacting the disk space and performance.
            
            The following operations are performed on this database:
            
            1. A large ETL process that runs every night, which transforms and loads data into several tables.
            2. A data archiving job that runs every night, which removes old data from several tables.
            3. Frequent read/write operations during the day as part of normal business operations.
            
            Given this scenario, which of the following strategies could help manage the transaction log growth effectively?

A: Switch to the Simple recovery model.
            B: Schedule frequent log backup and cleanups during business hours.
            C: Shrink the transaction log file size during business hours.
            D: Increase the database file size.