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.

Common challenges in data validation during ETL processes include ensuring data quality, managing large data volumes efficiently, dealing with data latency issues, and maintaining data lineage.

Database testing verifies the accuracy, consistency, and integrity of data within applications, helping to identify and mitigate issues such as data corruption and inconsistency. It ensures that data is reliable and secure, thus reducing the risk of data-related problems impacting application functionality.

SQL is commonly used for writing test scripts in database testing because it is specifically designed for querying and manipulating data in databases. Test scripts often involve executing SQL queries to verify the functionality, performance, and integrity of database operations. SQL's syntax and capabilities make it an ideal choice for database testing tasks.

Data comparison testing involves comparing data between two systems, databases, or datasets to identify discrepancies, such as missing or duplicate records. This is crucial for ensuring data integrity and accuracy. It helps detect inconsistencies that may occur during data transfer or transformation processes. Hence, it's an essential technique in database testing for identifying data integrity violations.

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.