The term "Data Dictionary" in database schema testing refers to a catalog that contains metadata about all data elements and data structures in the database. It provides information such as data types, relationships between tables, constraints, etc. This information is crucial for understanding and validating the database schema during testing.

While indexes can significantly improve query performance, adding too many can lead to increased disk space usage, slower data modification operations (inserts, updates, deletes), and higher memory consumption. Additionally, excessive indexes can cause index fragmentation, leading to reduced query performance.

In database systems, an index provides a data structure that allows for faster data retrieval based on key columns. Indexes are created on columns frequently used in queries to speed up data retrieval operations. By organizing data in a structured manner, indexes enable the database engine to quickly locate and access the desired information without having to scan the entire dataset.

Inadequate database testing can lead to data corruption, resulting in data loss or data integrity issues. Data corruption can compromise the reliability and functionality of the application, leading to errors and failures.

A test progress report provides a summary of the progress made during testing, including the number of test cases executed, how many passed, and how many failed. It gives stakeholders a quick overview of the testing status and helps in tracking the overall progress of the testing effort. This report is crucial for project managers and stakeholders to assess the current state of the project and make informed decisions about the release readiness.

SQLUnit: SQLUnit is a database testing tool specifically designed for unit testing of SQL queries. It provides a framework for writing and executing unit tests for SQL code, helping developers ensure the correctness and reliability of their SQL queries.

Functional testing is the type of SQL testing that verifies the correctness of SQL queries. It ensures that the SQL queries perform the intended operations accurately and return the expected results. Functional testing involves testing individual functions or features of the software to validate their behavior according to the specified requirements.

In database testing, ensuring the integrity of data is crucial. This involves validating that the data stored in the database is accurate, consistent, and adheres to constraints such as primary key constraints, foreign key constraints, and data types. Verifying data completeness, consistency, and security are all part of ensuring data integrity.

The correct SQL statement for deleting records from a table based on a condition is "DELETE FROM Employees WHERE." This statement allows you to specify a condition, such as salary being below a certain threshold, and deletes all matching records from the "Employees" table.

Database schema testing involves examining the connections or relationships between various tables to ensure that data consistency is maintained across the database. Relationships define how data in one table relates to data in another.