Describe the process of eliminating partial dependencies in a database.

The process of eliminating partial dependencies in a database involves the normalization of the database schema. Normalization is a technique used to organize and structure the data in a database to minimize redundancy and improve data integrity.

Partial dependencies occur when a non-key attribute is functionally dependent on only a part of the primary key. In other words, a partial dependency exists when a non-key attribute is determined by only a subset of the primary key, rather than the entire key.

To eliminate partial dependencies, we need to follow a series of normalization steps, typically starting with the first normal form (1NF) and progressing to higher normal forms such as the second normal form (2NF) and third normal form (3NF). Here is a step-by-step process to eliminate partial dependencies:

1. First Normal Form (1NF):
- Ensure that each attribute in a table contains only atomic values (i.e., indivisible values).
- Remove repeating groups by creating separate tables for them.
- Identify a primary key for each table.

2. Second Normal Form (2NF):
- Ensure that the table is in 1NF.
- Identify and remove any partial dependencies.
- Create separate tables for the attributes that are functionally dependent on only part of the primary key.
- Establish relationships between the tables using foreign keys.

3. Third Normal Form (3NF):
- Ensure that the table is in 2NF.
- Identify and remove any transitive dependencies.
- Create separate tables for the attributes that are functionally dependent on other non-key attributes.
- Establish relationships between the tables using foreign keys.

4. Higher Normal Forms (4NF, 5NF, etc.):
- Continue the normalization process to higher normal forms if necessary, depending on the complexity and requirements of the database.

By following these normalization steps, we can eliminate partial dependencies and ensure that the database schema is well-structured, efficient, and free from redundancy. Normalization helps in improving data integrity, reducing data duplication, and facilitating efficient data retrieval and manipulation operations.