What is Normalization in SQL: Meaning and Types
Search Query Language is a programming language that manages and manipulates data in relational databases, allowing users to create, read, update, and delete data and define database structures. It has widespread applications in diverse industries, including finance, healthcare, e-commerce, retail, and education. The value of SQL lies in its scalability, reliability, standardization, flexibility, efficiency, and security, pushing it as an essential tool for handling and analyzing extensive data sets. This blog is briefly about normalization in SQL and its types.
Normalization in SQL
Normalization is a fundamental concept in database design. In SQL, normalization is logically and efficiently structuring data in a database.
Types of Normalization
Normalization has various levels defined by specific rules known as Normal Forms. Generally, the six most common Normal Forms followed. By following these steps, we can complete the normalization process.
● First Normal Form (1NF):
Identifies and ensures that every table has a primary key and every column contains atomic values (i.e., values that cannot be subdivided).
● Second Normal Form (2NF):
Ensures that every non-key column in the table depends on the entire primary key functionally.
● Third Normal Form (3NF):
Ensures that every non-key column is not functionally dependent on other non-key columns.
● Boyce-Codd Normal Form (BCNF):
Every determinant is a candidate key in this intense Normal Form of 3NF.
● Fourth Normal Form (4NF):
Deals with multivalued dependencies.
● Fifth Normal Form (5NF):
Deals with cases where a composite key is required and where there are an overlapping candidate
Domain-Key Normal Form (DK/NF) and Sixth Normal Form (6NF) are higher levels of normalization form of 5NF. These can provide further benefits in particular cases. But these two are used infrequently. Higher levels of normalizations always did not result in a more efficient database structure. Sometimes denormalization (i.e., purposely doing redundancy into the database) is required for performance reasons. However, normalization is generally considered the best approach.
Significance of Normalization
Normalization is reducing the repeated data, allocating a single location to only one copy of each data in the database, and optimizing database structure by splitting enormous tables into smaller, more manageable tables and establishing relationships between them. This action enhances data consistency, integrity, and storage requirements and eases maintenance. Furthermore, it increases query performance and efficient data retrieval due to less process time.
Demerits of Normalization
Creating additional tables to eradicate data redundancy leads to higher storage costs and longer processing times. Moreover, normalization can reduce query performance when queries involve multiple tables. As a result, this measure can be slower than retrieving data from a single table.
In overview, normalization in SQL has its merits and demerits. Generally, it is considered a critical technique for structuring efficient and reliable databases. Normalization ensures a lot by following a set of rules and guidelines for database design. However, it is mandatory to resolve the potential drawbacks of normalization.
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