Relational database normalization is a systematic process of organizing data in a database to minimize redundancy and dependency, improve data integrity, and enhance consistency. It involves breaking down a table into smaller, more focused tables and defining relationships between them.

Key Goals of Normalization:

• Eliminate Redundant Data: Reduce duplication of information, saving storage space and preventing inconsistencies.
• Prevent Update Anomalies: Ensure updates are correctly reflected across all related data, maintaining consistency.
• Enforce Data Integrity: Maintain accurate and reliable data by enforcing constraints and relationships.
• Simplify Data Management: Make data easier to query, understand, and modify for users and applications.

Normal Forms:

Normalization involves progressing through a series of "normal forms," each with specific rules for table structure:

1. First Normal Form (1NF):
   • Each column contains atomic values (single, indivisible units).
   • No repeating groups of data in a single column.
2. Second Normal Form (2NF):
   • Meets 1NF requirements.
   • No non-key columns are functionally dependent on a partial key (only depends on the full primary key).
3. Third Normal Form (3NF):
   • Meets 2NF requirements.
   • No non-key columns are transitively dependent on the primary key (no indirect dependencies).
4. Boyce-Codd Normal Form (BCNF):
   • A stricter version of 3NF, ensuring that determinants (columns that functionally determine other columns) are candidate keys.
5. Higher Normal Forms (4NF, 5NF, ...):
   • Address more specific anomalies and dependencies, but often less practical in real-world applications.

Best Practices:

• Normalize to a suitable level based on data complexity and application needs (business rules).
• Consider performance implications and balance with data integrity goals.
• Use database design tools and techniques to guide the normalization process.
• Regularly review and adjust normalization as data and requirements evolve.