In a functional dependency, if B is dependent on A and removing an attribute from A still maintains the dependency, what is this condition called?

In a functional dependency, if B is dependent on A and removing an attribute from A still maintains the dependency, what is this condition called?

• A. Functional dependency
• B. Partial functional dependency
• C. Insertion anomaly
• D. Normal form

Answer: (B)

The correct answer is partial functional dependency. In the context of relational databases, a functional dependency defines a relationship between two attributes, typically between a primary key and a non-key attribute. When we say that B is dependent on A, it means that for every value of A, there is a consistent value of B. Partial functional dependency occurs when an attribute is dependent on part of a composite primary key, rather than on the whole key. In this scenario, if removing some part of A still allows B to be functionally determined by A, it indicates that B does not rely on the entire composite key but rather on a subset of it. This situation can lead to design issues, such as redundancy and the potential for anomalies in data manipulation. Understanding partial functional dependency is crucial for database normalization, as it helps identify situations where the database schema can be improved to ensure that data is organized more efficiently, thereby reducing redundancy and improving data integrity.

The correct answer is partial functional dependency. In the context of relational databases, a functional dependency defines a relationship between two attributes, typically between a primary key and a non-key attribute. When we say that B is dependent on A, it means that for every value of A, there is a consistent value of B.

Partial functional dependency occurs when an attribute is dependent on part of a composite primary key, rather than on the whole key. In this scenario, if removing some part of A still allows B to be functionally determined by A, it indicates that B does not rely on the entire composite key but rather on a subset of it. This situation can lead to design issues, such as redundancy and the potential for anomalies in data manipulation.

Understanding partial functional dependency is crucial for database normalization, as it helps identify situations where the database schema can be improved to ensure that data is organized more efficiently, thereby reducing redundancy and improving data integrity.