The TRY...CATCH statement is commonly used in SQL to catch and handle errors. It allows developers to encapsulate the code that might generate errors within a TRY block and specify the actions to be taken in case an error occurs in the corresponding CATCH block. This helps in better error handling and ensures that the application remains stable even in the presence of errors.

The DELETE statement in SQL is used to remove one or more rows from a table in a database. It is a Data Manipulation Language (DML) statement that allows users to remove unwanted data from a table, based on a specified condition if needed.

Extraction is the correct option. In the ETL (Extract, Transform, Load) process, the first step is to extract data from the source systems. This involves identifying the relevant data sources and pulling the required data into the ETL pipeline for further processing.

The primary function of an Intrusion Detection System (IDS) is to monitor and detect suspicious activities on a network or system for enhanced security.

Performance testing in databases primarily aims to assess the speed and responsiveness of the database system under various conditions such as heavy loads, concurrent users, or large datasets. Performance testing helps identify bottlenecks and optimize database performance.

Authentication testing involves validating the identity of a user or system to ensure that only authorized entities gain access. Verification is the process of evaluating if the requirements are met, while validation ensures that the system meets the user's needs. Authentication specifically deals with confirming the identity of users or systems accessing a resource. Authorization, on the other hand, pertains to granting access rights based on authenticated identities.

Data Integrity Testing in database testing primarily focuses on verifying the accuracy and consistency of data within the ETL (Extract, Transform, Load) processes. It ensures that data is correctly extracted, transformed, and loaded into the target database without any loss or corruption.

Diverse data sources pose a significant challenge in ETL data validation. These sources may have varying formats, structures, or data quality, making it complex to validate and ensure the consistency and integrity of data across different sources during the ETL process. Testers need to address this challenge effectively to ensure accurate data validation.

An INNER JOIN retrieves records from both tables where there is a match between the columns specified in the JOIN condition. Since you need to find customers who have placed orders, you want to retrieve records from both the "Customers" and "Orders" tables where there is a match on the customer ID in both tables, making INNER JOIN the appropriate choice.

The WHERE clause is used to filter rows based on a specified condition. In this scenario, you would use the WHERE clause to specify the date range for which you want to calculate the total revenue from the "Sales" table. This clause ensures that only the relevant rows within the specified date range are included in the calculation.