Database SQL Design: A Comprehensive Guide to Normalizing Your Data

Introduction

When it comes to designing a database for your application, one of the most important decisions you’ll make is how to structure your tables. This is particularly relevant when working with complex data entities that have multiple relationships between them. In this article, we’ll explore the pros and cons of different approaches to normalizing your data, including whether to create separate tables for users and banks or to store banking information within the user table.

Understanding Normalization

Before we dive into the specifics, let’s define what normalization is in the context of database design. Normalization is the process of organizing your data into a structured format that minimizes redundancy and dependency between different pieces of data. The goal is to ensure that each piece of data is stored in one place and one place only, making it easier to maintain consistency across your application.

Case 1: Storing Banking Information within the User Table

One possible approach is to store all the banking information for a user directly within their table. This might look like this:

User(uid, name, lastname, bio, url_img, IBAN_number, bank_name, bank_location)

However, as the answer to the original Stack Overflow post pointed out, this approach has several drawbacks. For example:

• A user cannot exist without a bank. By storing banking information within the user table, you’re creating redundancy and making it difficult to maintain consistency.
• If multiple banks are used for the same user, you’ll end up with duplicate data.

Case 2: Creating Separate Tables for Users and Banks

Another approach is to create separate tables for users and banks. This might look like this:

User(uid, name, lastname, bio, url_img)

Bank(bank_id, name, location)

However, as the answer also pointed out, this approach has its own set of issues. For example:

• A user can exist without a bank, but it’s still logical that a bank should have at least one user.
• If multiple banks are used for the same user, you’ll end up with redundant data.

The Ideal Solution: Normalizing Banking Information

So, what’s the ideal approach? To normalize banking information while maintaining consistency and minimizing redundancy. One possible solution is to create a separate table that stores user-bank relationships:

User(uid, name, lastname, bio, url_img)

Bank(bank_id, name, location)

UserBank( user_id, bank_id, account_no, iban_number, ... )

In this approach, we’ve created a new table called UserBank that stores the relationship between users and banks. This allows us to:

• Store unique banking information for each user without duplicating data.
• Establish a clear and consistent way of modeling user-bank relationships.

Alternate Key (Unique) Constraints

One important aspect of this design is the use of alternate key constraints (also known as uniqueness constraints). An alternate key is a column or set of columns that uniquely identifies a record within a table. In our case, we’ve used user_id and bank_id as alternate keys in the UserBank table.

By applying an alternate key constraint to these columns, we ensure that each combination of user_id and bank_id is unique across all records in the table. This helps prevent data inconsistencies and makes it easier to maintain accurate information.

Foreign Key (FK) Constraints

Another important aspect of this design is the use of foreign key constraints (also known as referential integrity constraints). A foreign key is a column or set of columns that references another column or set of columns in a different table. In our case, we’ve used user_id and bank_id as foreign keys in the UserBank table.

By applying foreign key constraints to these columns, we establish a clear relationship between the user bank data and the underlying user and bank tables. This helps prevent data inconsistencies and ensures that changes made to one table are reflected in all dependent tables.

Example Use Cases

Here are some example use cases for this normalized design:

• User Profile Page: When displaying a user’s profile page, you can retrieve their relevant banking information (e.g., account number, IBAN) from the UserBank table using the user_id.
• Transaction History: To display a user’s transaction history, you can join the UserBank table with the underlying bank table to retrieve additional information (e.g., bank name, location).
• Account Management: When managing an account for a user, you can use the UserBank table to retrieve the current account number and IBAN.

Conclusion

Normalizing your database design is crucial for maintaining consistency, minimizing redundancy, and ensuring data integrity. By understanding the pros and cons of different approaches to normalizing your data, including whether to create separate tables for users and banks or to store banking information within the user table, you can make informed decisions about your application’s database design.

In this article, we’ve explored a normalized design that stores user-bank relationships in a separate table called UserBank. By applying alternate key constraints and foreign key constraints, we establish a clear and consistent way of modeling these relationships. This design provides a solid foundation for building robust and maintainable applications.

Last modified on 2023-10-18