Database Normalization

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 Understanding the Basics and Advanced Levels of Database Normalization


If you’re new to database design, you’ve probably heard about database normalization. This is the process of organizing data in a database so that it is consistent, efficient, and easy to manage. There are several levels of normalization, each with their own benefits and use cases. In this article, we’ll cover the basics of normalization, including first normal form (1NF), second normal form (2NF), third normal form (3NF), and other advanced normal forms.

Normal Form

Concept of normalization and normal forms were introduced, after the invention of the relational model. Database normalization is an essential procedure to avoid inconsistency in a relational database management system. It should be performed in the design phase. To achieve this, redundant fields should be refactored into smaller pieces.

Normal forms are defined structures for relations with set of constraints that relations must satisfy in order to detect data redundancy and correct anomalies. There can be following anomalies while performing a database operation:

  • insert - data is known but can not be inserted
  • update - updating data requires modifications in multiple tuples (rows)
  • delete - deleting some data causes some other data to be lost

First Normal Form has initial constraints, further normal forms like 2NF, 3NF, BCNF, 4NF, 5NF would add new constraints cumulatively. In other words, every 2NF is also in 1NF; every relation in 3NF is also in 2NF. If all group of relations are represented as sets, following figure can be drawn


First Normal Form (1NF)

First normal form (1NF) is the simplest level of normalization. It involves ensuring that each table in the database has a primary key and that each column in the table contains atomic values. In other words, each row in the table should have a unique identifier, and each value in the table should be indivisible.

Let’s take an example to understand this better. Consider a table that stores information about employees. The table might have columns like employee_id, name, address, and phone_number. 

The Unnormalized Table

Imagine you have a table that stores information about employees. Here’s what the unnormalized table might look like





Rule for 1NF

The key rule for 1NF is that each column should contain only atomic (indivisible) values. No columns should have multiple values for a single record.

Applying First Normal Form (1NF)

To bring this table into 1NF, we need to make sure that each column contains only one value per row. This can be done by splitting the phone_number column into multiple rows, ensuring that each phone number appears in a separate record.


Now, each row contains atomic values, with one employee and one phone number per record. This table conforms to 1NF. 

Benefits of First Normal Form (1NF)

1NF ensures that the data in your table is more organized and easier to manage. Here are a few key benefits:

  • Eliminates Redundancy - Reducing data repetition makes the table more efficient and prevents inconsistencies.
  • Improved Data Integrity - With each value properly isolated, the database enforces a stricter structure, minimizing errors.
  • Easier Queries - Querying for specific information, such as retrieving a particular phone number, becomes more straightforward when the data is properly normalized.

Conclusion

Applying First Normal Form (1NF) is a crucial first step in structuring a database. It ensures that data is stored in a way that eliminates repetition and maintains data integrity by enforcing atomic values. While 1NF is just the beginning of the normalization process, it lays the foundation for a well-organized database.

In our example, the employee table transformed from an unnormalized structure into one that adheres to 1NF, making the data easier to manage and query.


-- Thank You --

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