SQL Injection is a security vulnerability where attackers insert malicious SQL code into input fields, such as login forms or search queries, to manipulate the database and perform unauthorized actions. This vulnerability can lead to data breaches, data loss, or unauthorized access to sensitive information stored in the database. Preventative measures include parameterized queries, input validation, and using ORM frameworks.

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.

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.

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.

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.

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.

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.

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.

Database testing ensures the integrity of data, ensuring that it maintains its accuracy, reliability, and consistency throughout various operations such as insertion, deletion, and retrieval.

Authorization testing verifies that only authorized users have access to the database. It involves validating user credentials, permissions, and roles to prevent unauthorized access.

Implementing covering indexes ensures that all required columns for a query are included in the index itself, eliminating the need to access the actual table data for retrieval. This approach enhances query performance without affecting data insertion speed.

Indexing improves database query performance by speeding up data retrieval. It works by creating an optimized data structure that allows the database management system to locate rows more efficiently based on the indexed columns. This helps reduce the time required to execute queries, especially for large datasets, resulting in faster response times for users.