When discrepancies between database copies are detected during data consistency testing, it's essential to perform thorough data validation to resolve the issues. Data validation involves verifying the accuracy and consistency of data across different sources or copies by comparing them against predefined criteria or rules. This process helps in identifying and resolving discrepancies, ensuring that data remains consistent and reliable throughout the database system.

The rollback plan ensures the ability to return to the original state before data migration, which is crucial for mitigating risks in case of issues during the migration process.

Conducting root cause analysis is crucial in understanding why there has been a sudden increase in defect density. It helps identify underlying issues in the software development process, such as coding errors, inadequate requirements, or insufficient testing, allowing the team to take corrective actions effectively.

During test script execution, the results are compared to the Expected Results to determine pass or fail. Expected Results are predefined outcomes that indicate the correct behavior of the system under test. Comparing actual results with expected results helps identify deviations or defects in the system functionality.

Authentication testing involves validating whether the system correctly identifies and verifies users. The primary goal is to ensure that only authorized users gain access to the system or application.

One effective way to prevent SQL injection attacks in your applications is to use parameterized queries. Parameterized queries separate SQL code from user input, making it impossible for attackers to inject malicious SQL commands into input fields. By using placeholders for user input, parameterized queries ensure that user-supplied data is treated as data rather than executable code. Additionally, implementing input validation, using stored procedures, and employing web application firewalls are other strategies to mitigate the risk of SQL injection attacks.

ETL stands for Extract, Transform, Load. It is a crucial process in data warehousing and database testing where data is extracted from various sources, transformed according to business rules, and loaded into a target database or data warehouse for analysis and reporting purposes.

It's important to ensure that test data generation tools comply with data privacy regulations when handling sensitive information. Compliance with privacy regulations ensures that sensitive data is handled appropriately and securely during the testing process.

Database authorization is the process of granting or denying access to specific data based on the user's role and permissions. It ensures that only authorized users can access the data they are allowed to see, thus making option 3 the correct choice.

Authorization testing focuses on evaluating whether users have the necessary permissions and privileges to access specific resources or perform certain actions within the system.