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.

The keyword commonly used in SQL to specify the order in which the result set should be returned is ORDER. This keyword is used in conjunction with ORDER BY clause in SQL queries to sort the result set based on one or more columns. By specifying the order, the database engine can efficiently retrieve and return the data in the requested sequence, potentially improving query performance.

NoSQL databases are often used for distributed data storage and retrieval in big data scenarios. Unlike traditional relational databases, NoSQL databases are designed to handle large volumes of unstructured or semi-structured data across distributed systems. They offer flexible data models, horizontal scalability, and high availability, making them well-suited for handling the complexities of big data environments. Examples of NoSQL databases include MongoDB, Cassandra, and HBase.

Mandatory Access Control (MAC) is commonly used in government and military systems. In MAC, access to resources is based on the security classification assigned to the user and the security classification assigned to the resource. Users are only able to access resources for which they have clearance. This model ensures that access is based on a need-to-know basis, as users can only access resources that are deemed appropriate based on their clearance level.

Query tuning involves analyzing and modifying SQL queries to make them more efficient in terms of execution time and resource usage. This process often involves examining query execution plans, indexing strategies, and data retrieval methods to optimize performance.

Checksums are a method used to detect errors in data transmission or storage by calculating a unique value based on the content of the data. Comparing checksums before and after transmission or storage helps identify any changes or corruption that may have occurred.

Data consistency and accuracy are crucial aspects of database testing. Implementing data validation checks ensures that the data entered into the database meets certain criteria, thus maintaining consistency and accuracy. This involves validating data types, constraints, and relationships to ensure they adhere to predefined standards. Performing data reconciliation helps identify discrepancies between different datasets or systems, aiding in maintaining data accuracy.

A SELF JOIN is a regular join but with a table being joined to itself. In this scenario, you can use a SELF JOIN on the employee table, matching the ManagerID in the table to the ID of another employee to retrieve the names of all employees and their respective managers.