Encryption is a database security mechanism that focuses on converting data into a format that is unreadable without the appropriate decryption key. By encrypting sensitive data, even if unauthorized users gain access to the database, they cannot interpret the information without the decryption key, thus enhancing data protection.

Transformation involves converting data from its source format to the target format. This step typically includes data cleaning, filtering, aggregation, and other operations to prepare the data for storage or analysis.

Throughput is a commonly used metric to measure the scalability of a system. It refers to the number of units of work completed per unit of time and indicates how effectively a system can handle an increasing workload. Higher throughput generally signifies better scalability as the system can process more requests or transactions in a given timeframe.

The primary purpose of the "Extract" phase in the ETL process is to retrieve data from multiple sources. This involves extracting data from various operational systems, databases, or external sources such as files or APIs. The extracted data is then prepared for the subsequent transformation phase, where it will be cleansed, validated, and transformed into a consistent format suitable for storage and analysis in the target database or data warehouse.

The "credential validation" step in authentication testing is crucial as it verifies the user's identity by checking the provided credentials against the stored credentials in the system. It ensures that only authorized users with valid credentials can access the system, enhancing security and preventing unauthorized access.

Scalability testing evaluates a system's ability to handle increased workload, such as a growing number of concurrent users, and larger data volumes without compromising performance or stability. By conducting scalability testing, organizations can identify potential bottlenecks and optimize their systems to accommodate future growth effectively.

Data replication is the term commonly used for the process of storing and managing large data sets across multiple servers or nodes. It involves duplicating data across different servers to ensure redundancy and fault tolerance, thereby enhancing availability and reliability in distributed database systems.

ETL testing is crucial in the data integration process because it ensures the accuracy of data. By validating data accuracy, it ensures that the transformed data maintains its integrity throughout the ETL process.

Indexing is a technique used to improve the speed of data retrieval operations on a database table at the cost of additional writes and storage space. By adding indexes to the columns involved in the query's WHERE clause or JOIN conditions, you can significantly speed up query execution. Thus, considering indexing is crucial when optimizing a slow-running SQL query.

Parameterized Queries are a powerful defense mechanism against SQL injection attacks in web applications. They involve the use of placeholders for user input in SQL queries, which are then bound to parameter values at runtime. This prevents malicious input from being interpreted as part of the SQL query, effectively mitigating SQL injection attacks.