Databases come with pros and cons. For one, they can be a handy way to organize large amounts of important numbers and figures. However, if that database isn’t organized properly, it can be quite difficult to work with. For those who rely on a database management system (DMBS) in their day-to-day operations, you know how important it is for that database to be organized cohesively and efficiently.
Without that organization, it can be incredibly difficult to find the information you need. Cohesion and efficiency help to make sure that you don’t have to spend more time than you need searching through your DBMS, wasting precious time and energy that could be spent on the task at hand instead. Thankfully, there’s database normalization. But what is database normalization, and how does it work? Where did it originate from, and how can you normalize your DBMS? This guide will explain everything you need to know.
What is Database Normalization?: Complete Explanation
Simply put, database normalization is the process of organizing a database’s columns and tables. In doing this, the database’s dependencies are correctly carried out by the integrity constraints of the database. This normalization of the database is achieved by implementing hard and fast rules. There are two ways to enforce these rules: synthesis, which requires an entirely new design for the database, or decomposition, which requires improvements to an existing design for the database.
To achieve database normalization, the database needs to be organized according to something called normal forms. Typically, normalization calls for three types of (or stages of) normal forms: 1NF, 2NF, and 3NF. Each of these types of normal forms comes with its own set of rules. They are as follows:
First Normal Form (1NF)
- Each column has single values
- Each column has a different name
- Each given attribute’s value must come from the same type of data
- No two rows can be alike
Second Normal Form (2NF)
- The database is in its first normal form.
- The database is free from any partial dependency. (Partial dependency is what happens when a non-prime attribute is functionally dependent on the part of a candidate key. A non-prime attribute isn’t part of a candidate key.)
Third Normal Form (3NF)
- The database is in second normal form.
- The database doesn’t have a transitive dependency. (Transitive dependency is when two values in the same table have an indirect relationship that creates a functional dependency. Functional dependency is a direct constraint between two attributes.)
Beyond these three most essential types of normal forms, there’s also a fourth type: Boyce and Codd Normal Form, or BCNF. BCNF is essentially an upgraded version of 3NF, designed to deal with a database anomaly that isn’t addressed by 3NF. For a table to meet the BCNF requirement, it needs to be free from multiple overlapping candidate keys. In other words, BCNF requires:
- The database is in third normal form.
- For every functional dependency X -> Y, X should be a super key. (A super key is one or more sets of columns in a table that can uniquely identify a row.
There are other normal forms beyond these (going all the way to the sixth normal form), but these first three or four are undoubtedly the most essential for database normalization.
Database Normalization: An Exact Definition
Database normalization is constructing a database — typically a relational one — with normal forms in mind. This is done to cut down on redundancy in the data and maximize the data’s integrity.
How Does Database Normalization Work?
Database normalization works by establishing tables and defining the relationships between the tables by the rules of normal forms. In doing this, you can keep the data cohesive and efficient by getting rid of any redundancies or inconsistent dependencies. An efficient organization is everything when it comes to a DBMS, and without database normalization, you run the risk of working with a confusing, disorganized, inefficient database. Working with one of these wastes precious time, making database normalization a necessity.
Database normalization works much like a mathematical equation. These rules of normal form detailed above are logical, meaning that they’re guaranteed to be accurate and truthful, and free from any miscalculations or errors in the database. Without this logic, your database will be more susceptible to mistakes and misunderstandings. This could be disastrous for you and your data.
How Do You Create Database Normalization?
To establish database normalization, you must apply the rules of the first, second, and third (and, if relevant, Boyce and Codd) normal form. These steps are designed to create database normalization, and skipping even a single step could result in a database that isn’t normalized.
Start by looking at individual tables and getting rid of any repeating groups. Then, establish every set of related data in its separate table. After that, identify the primary key of each related data set. This is the first normal form.
Next, make different tables for each value set that applies to multiple records. Then, use a foreign key to link these tables. This is the second normal form. After that, get rid of any data fields that don’t depend on the key. This is the third normal form.
Where Did Database Normalization Originate From?
The first normal form was defined in 1970 by Edgar F. Codd. The goal was to allow data to be examined and altered with a logical data sub-language. SQL is one such example of one of these sub-languages, although Codd considered SQL to be seriously flawed and wanted something far more logical. Still, most relational databases continue to use SQL (despite Codd’s legitimate analysis of the sub-languages pros and cons).
Throughout the 1960s and ‘70s, Codd toiled away on his data arrangement theories, eventually publishing a paper titled “A Relational Model of Data for Large Shared Data Banks” with his findings. While his work was initially balked at, it eventually caught on in a major way. As a result, Codd’s work is widely recognized and practiced (and he even has a normal form named after him!).
What Are the Applications of Database Normalization?
Database normalization is an essential part of everyday database management. If you work with a database, there are no pros and cons to this normalization process: It’s only a positive. Normalization is an absolute must because it guarantees that a database only contains numbers and figures that relate directly to the primary key. Beyond this, normalization also ensures that each field of data contains a single data element. Normalization also makes sure to remove any repeating or irrelevant data. In short, these are the applications of database normalization: ensuring cohesive, efficient data in a database.
Examples of Database Normalization In the Real World
If all of this mathematical jargon sounds a little confusing, here are some examples of database normalization in the real world to help it make sense.
Managing a Customer’s Orders
Database normalization can help keep track of a customer’s orders. Rather than re-writing the customer’s name, address, and card info with every new order, a business could create tables for their customer’s data with a corresponding ID number for each customer. That way, their order, name, address, and card info could all change, but their ID number would link it all together. That ID is the primary key.
Organizing a Company’s Employees
Similar to the above example, a company can effectively organize all its employees in a database with an ID number for each employee. This ID number should remain the same no matter how the employee’s address, phone number, or marital status might change over time. Again, that ID is the primary key.
Keeping Track of Rentals
A video store or library would benefit from database normalization to properly keep track of who has checked out which items. With a membership card and corresponding ID number acting as the primary key, the library or video store can keep a record of a person and their rentals with ease.