Скачать или смотреть Demystifying Database Normalization: Achieving Data Efficiency and Integrity

Normalization is a process used in various fields, such as database design or statistics, to bring data into a specific standard or form to reduce redundancy and improve efficiency. The conditions for normalization typically refer to the normal forms in database design, specifically First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), and so on.

Here are some key conditions for achieving different normal forms in a relational database:

First Normal Form (1NF):

Each column in a table must contain atomic (indivisible) values.

There should be no repeating groups or arrays within a column.

Second Normal Form (2NF):

The table must already be in 1NF.

All non-key attributes (columns) must be fully functionally dependent on the entire primary key.

Third Normal Form (3NF):

The table must already be in 2NF.

There should be no transitive dependencies, meaning that non-key attributes should not depend on other non-key attributes.

Beyond 3NF, there are further normal forms like Boyce-Codd Normal Form (BCNF) and Fourth Normal Form (4NF), which have their own specific conditions.

The goal of normalization is to eliminate data anomalies, such as redundancy and update anomalies, while ensuring data integrity and efficient data storage. Depending on the specific use case and database design, you may choose to normalize data to different

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