Database Normalisation Questions Medium
There are several common mistakes to avoid in database normalization. These include:
1. Over-normalization: Over-normalization occurs when a database is excessively broken down into smaller tables, resulting in unnecessary complexity and decreased performance. It is important to strike a balance between normalization and practicality.
2. Ignoring functional dependencies: Functional dependencies are relationships between attributes in a database. Ignoring these dependencies can lead to data redundancy and anomalies. It is crucial to identify and properly handle functional dependencies during the normalization process.
3. Lack of proper primary keys: Every table in a normalized database should have a primary key that uniquely identifies each record. Failing to define proper primary keys can result in data integrity issues and difficulties in querying the database.
4. Ignoring data integrity constraints: Data integrity constraints, such as unique constraints and foreign key constraints, ensure the accuracy and consistency of data in a database. Neglecting to enforce these constraints can lead to data inconsistencies and errors.
5. Failure to consider performance implications: While normalization improves data integrity and reduces redundancy, it can also impact performance. It is important to consider the performance implications of normalization decisions, such as the number of joins required for queries, and strike a balance between normalization and performance.
6. Lack of documentation: Proper documentation is essential for understanding the database structure and relationships. Failing to document the normalization process can make it difficult for future developers or administrators to maintain and modify the database.
By avoiding these common mistakes, database designers can ensure that the normalization process is effective, resulting in a well-structured and efficient database system.