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.

Authentication in database security involves verifying the identity of users before granting access rights, ensuring that only authorized individuals can access the database.

Test data management is a critical aspect of automation frameworks as it ensures the availability of relevant and valid test data for executing test cases. Effective management of test data enhances the reliability and effectiveness of automated testing processes.

A cost-based query optimizer evaluates different ways to execute a query and chooses the one with the lowest estimated cost. It considers factors such as available indexes, table sizes, and statistical information to estimate the cost of various execution plans. By selecting the plan with the lowest estimated cost, it aims to improve query performance.

Encryption is commonly assessed during compliance testing to ensure data confidentiality. Encryption involves converting sensitive data into a secure format that can only be accessed with the appropriate decryption key. By encrypting data at rest and in transit, organizations can protect against unauthorized access and maintain compliance with regulatory requirements related to data privacy and confidentiality. Compliance testing evaluates the implementation of encryption mechanisms, such as encryption algorithms, key management practices, and data encryption policies, to ensure adequate protection of sensitive information.

Authorization ensures that only authorized users can access specific data within a database. Authentication verifies the identity of users before granting access rights.

When a previously passing test script fails unexpectedly, verifying recent changes in the application code or database schema is crucial. Any modifications or updates could have introduced errors or inconsistencies, leading to the failure. By reviewing the changes, developers and testers can pinpoint potential causes and take corrective actions promptly. This ensures the stability and reliability of the test scripts and the overall application.

Intermittent test failures in database scripts could result from data dependencies or conflicts arising from concurrent test executions. When multiple tests manipulate the same data simultaneously, it can lead to inconsistent outcomes, causing intermittent failures. To troubleshoot this issue, identifying and resolving data dependencies, ensuring proper synchronization between test steps and transactions, and implementing mechanisms to manage concurrent access to shared data are essential steps. This ensures test scripts execute reliably and produce consistent results.

Handling large data sets in a database often poses the challenge of scalability, where traditional database systems struggle to efficiently manage and process vast amounts of data. Scalability refers to the ability of a system to handle increasing amounts of workload or data without compromising performance or responsiveness.