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SQL Advanced: Normalization

Learn concept of Normalization with MariaDB server/client and pre-created SQL scripts

228 Participants 30 Minutes Beginner

Just as SQL databases use tables to store data neatly, Normalisation takes data organisation to the next level. This lab will delve into the fundamentals of Normalisation with MariaDB, guiding you through essential operations and helping you understand the power of well-structured databases.

 

Prerequisites:

Before diving into this lab, we recommend completing the SQL Basics lab as it covers essential concepts used in Normalization. Familiarity with the Docker Basics lab is also beneficial.

 

 

Understanding Normalisation:

Normalisation is like tidying up a messy room, but for your database. It involves breaking down large, complex tables into smaller, related tables to reduce redundancy and improve data integrity. Think of it as a system that ensures every piece of data has its rightful place, making data retrieval and manipulation more efficient.

 

Primary Keys:

Just like in SQL, primary keys play a vital role in Normalisation. They are unique identifiers for each row in a table and serve as the glue that connects related tables together.

 

Benefits of Normalization:

Data Integrity:

Normalization prevents data duplication and maintains data accuracy, reducing the risk of errors and inconsistencies.

Efficiency:

Smaller, well-structured tables are easier to query, leading to faster and more efficient data retrieval.

Scalability:

Normalized databases are highly adaptable and scalable, making them suitable for a wide range of applications.

 

Levels of Normalization:

Normalization is divided into different levels or forms, each with its own set of rules. The most common forms are:

First Normal Form (1NF):

In 1NF, data is organized so that each table column contains only atomic, indivisible values. It eliminates complex data types and ensures each cell holds a single piece of data, preventing arrays or nested structures.

Second Normal Form (2NF): 

Building upon 1NF, 2NF eliminates partial dependencies. It divides data into separate tables, linking related records through primary and foreign keys, thereby removing redundancy and improving data integrity.

Third Normal Form (3NF):

3NF goes a step further by removing transitive dependencies. It ensures that non-key attributes depend only on the primary key, minimizing data duplication and maintaining logical consistency.

Boyce-Codd Normal Form (BCNF):

BCNF is an advanced form addressing complex scenarios. It requires that non-key attributes be functionally dependent on superkeys, enhancing database design robustness.

Fourth Normal Form (4NF):

4NF tackles multi-valued dependencies, where a single value in one table may map to multiple values in another. It further refines data organization, enhancing data integrity.

Fifth Normal Form (5NF):

Also known as Project-Join Normal Form (PJNF), 5NF deals with cases where data can be organized into more than one way. It optimizes database design by splitting data into smaller, self-contained tables, ensuring data consistency and efficiency.

 

Refer to these links to learn more:

1. What is Data Normalization? - GeeksforGeeks

2.Normal Forms: GeeksforGeeks

 

Summary

This lab explores the fundamentals of normalization, guiding you through essential operations and showcasing the power of well-structured data management. Normalization involves breaking complex tables into smaller, interrelated ones to reduce redundancy and enhance data integrity. Think of it as a meticulous system ensuring every piece of data has a designated place, resulting in more efficient data retrieval and manipulation. Primary keys, acting as unique identifiers, play a pivotal role in connecting related tables, just like in traditional SQL databases. So lets dive into the lab to understand these concepts practically.

SQL Advanced: Normalization

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