Implementing a database testing tool like SQLUnit or DbUnit can significantly reduce human errors in testing by automating repetitive tasks and ensuring consistency in test execution. This automation leads to time-saving, improved test coverage, and better debugging support, justifying the implementation to management.

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 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.

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.

SQL is commonly used for writing automation scripts in database testing. SQL (Structured Query Language) is specifically designed for managing and manipulating relational databases. It allows testers to interact with the database, execute queries, and validate the results, making it a preferred choice for database testing automation.

Version control systems like Git play a crucial role in database testing within a CI environment by tracking changes made to database scripts and configurations. They ensure that all changes are documented, provide a history of modifications, and facilitate collaboration among team members. By maintaining a centralized repository of database scripts, Git enables seamless integration with CI pipelines, allowing for automated testing and deployment of database changes.

Performance testing is conducted to evaluate the system's performance under various workloads. Stress testing, a subset of performance testing, specifically checks the system's response under extreme conditions, such as high loads or concurrent users. In this scenario, the observed issue suggests a need for performance testing, particularly stress testing, to identify and address the performance degradation under heavy concurrent usage.

When testing complex joins and subqueries, testers should assess data accuracy and correctness. Accuracy ensures that the data returned by the queries is correct and aligned with the expected results. It involves verifying that the joins and subqueries produce the intended outcomes without errors or discrepancies.

Not testing the database thoroughly can lead to data integrity issues. This means that the data stored in the database might be inaccurate, incomplete, or inconsistent, which can have serious implications for the functioning of applications relying on that data. For example, incorrect data could result in incorrect decisions being made by the application, leading to financial losses or reputational damage.

SQL injection is a type of security vulnerability that occurs when a malicious SQL query is inserted into input fields of a web application. Attackers can exploit this vulnerability to gain unauthorized access to the database or manipulate its contents. By injecting malicious SQL code, attackers can bypass authentication, extract sensitive information, modify or delete data, and even execute administrative tasks on the database server. Implementing input validation, parameterized queries, and using prepared statements are common techniques to prevent SQL injection attacks.

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.

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.