Data is the most important asset for companies and businesses in the modern world. Data is the currency through which these organizations thrive. Thus, this precious data and its assessment must be organized and managed properly.
The system that helps in this is called Database Management System (DBMS). It is a special type of software designed to effectively store, organize, and manage data in a structured and refined manner.
Normalization in DBMS (Database Management System) is one of its crucial parts. This is an excellent and quick way to structure and organize data efficiently in its databases.
In this blog, we will discuss Normalisation in DBMS and its types. We will further discuss these types and learn more about their utilization in data storage and management.
But before proceeding with the normalization and its types, we must understand what a Data Management System is.
So without any further ado, let us delve into the world of data science and understand the process of Data Management Systems and the role of Normalisation In DBMS.
What is a Data Management System?
The database management system is software that allows the user to store and effectively manage data. In simple terms, DBMS is just a computerized digital system for storing and managing data. This software allows users much freedom with their data and lets them execute various functions.
Database management systems can be categorized using a variety of characteristics. Here are some of the most commonly used DBMS systems.
Distributed database management system
A distributed DBMS is a collection of logically interconnected databases. These databases are spread across a network and are governed by a centralized database application. This type of DBMS allows for periodic synchronization of the data. This makes sure that any manipulation or change in a database anywhere in the world is updated in the database.
Hierarchical database management system
Hierarchical database management systems perform their organizational tasks based on a tree-like structure. Data storage can be either in the format of bottom-up or top-down. Parent-child relationship most simply represents it.
Network database management system
This database management system works by allowing a child to have multiple parents. This satisfies the need for having more complex relationships in the database.
Relational database management system
This DBMS is probably the most popular model when it comes to its fantastic user interface. This model is based on the concept of data normalizing in the columns and rows of the table. The Relational DBMS is very useful when the user needs a system that can hold plenty of data and be scaled.
Object-oriented database management system
Object-oriented management system defines itself by its name. Instead of storing the data in columns and rows, this model stores it in objects. This model of DBMS is based on the concept of object-oriented programming (OOP).
Now that we are familiar with the concept of Data Management Systems and its types, let us familiarize ourselves with Normalisation in DBMS and its types.
What is Normalisation?
The process of simplifying the connection between data pieces in a record is known as normalization. It replaces the record structure in the data collection with a much better and simpler version.
Normalization in DBMS works by making the table into more manageable parts. This process ensures that every single piece of data is stored only once, thus ensuring simpler record-keeping and data maintenance.
In simpler terms, Normalisation in DBMS is an efficient and simple way to manage and organize data so that there are no duplications and fewer discrepancies.
Let us now move on to the types of normalization in DBMS
Types of Normalisation in DBMS
There are six types of Normalisation in DBMS. These are:
First Normal Form (1NF)
When there are no repeated groups in a table, it is said to be in the First Normal Form (1NF). All repetitive columns or fields in an unauthorized table are removed and placed in a new table.
These newly formed tables rely on the parent table. The table keys should also be part of the parent table for the parent table and the derived tables to be connected.
In simpler terms, it makes sure that each cell in a table consists of only one unique piece of data, thus making each row non-repetitive.
Second Normal Form (2NF)
The Second Normal Form (2NF) is used when all non-key fields in a table are completely reliant on the whole key. The concept of this form is that all the fields that do not rely on the complete key are removed from the table and moved to another table whose key they rely on.
In simpler terms, 2NF builds on 1NF. It removes any fields with partial dependencies and moves them where they are fully dependent on the table key.
Third Normal Form (3NF)
A table is said to be in the Third Normal Form (3NF) when all the non-key fields are independent of each other and other non-key fields.
3NF builds on 2NF. It eliminates the dependencies of transitive nature and allows for the independence of non-key fields.
Boyce Codd Normal Form (BCNF)
BCNF is an extension of the Third Normal Form. However, the format of this is much more rigid. This means that every BCNF relation is also in 3NF.
This form ensures that every unique identifier is a candidate key, making it even more robust and efficient.
Fourth Normal Form (4NF)
The fourth Normal Form is an extension of BCNF. 4NF eliminates situations when a composite key of the record type contains more than one separate, multivalued fact regarding the same object.
Fifth Normal Form (5NF)
5NF is the highest level of normalization in DBMS. The Fifth Normal Form removes any potential abnormalities in the database by disintegrating the complex relationships into separate tables. This process allows for excellent data management and organization.
Normalization in DBMS is an important process that allows for optimal organization and management of data. Data redundancy is removed by applying various normalization types in Database Management Systems such as 1NF, 2NF, and BCNF. This allows for a highly organized and structured database with minimal redundancies and errors.