The second normal form (2NF) is a concept in database normalization, a process used to organize data in a relational database to minimize redundancy and ensure data integrity. To transform a relation (table) into the second normal form, the following conditions must be met:

1. The relation must be in the first normal form (1NF): This means the table should not contain any repeating groups, and all attributes must be atomic (each attribute contains only one value).

2. Every non-key attribute must depend fully on the entire primary key: This means no non-key attribute should depend on just a part of a composite key. This rule aims to eliminate partial dependencies.

Example of Second Normal Form

Let's assume we have an Orders table with the following attributes:

• OrderID (Primary Key)
• ProductID (part of the composite key)
• CustomerName
• CustomerAddress
• ProductName
• Quantity

In this case, the composite key would be OrderID, ProductID because an order can contain multiple products.

To bring this table into the second normal form, we need to ensure that all non-key attributes (CustomerName, CustomerAddress, ProductName, Quantity) fully depend on the entire composite key. If this is not the case, we need to split the table.

Step 1: Decompose the Orders table:

1. Create an Orders table with the attributes:

   • OrderID (Primary Key)
   • CustomerName
   • CustomerAddress

2. Create an OrderDetails table with the attributes:

   • OrderID (Foreign Key)
   • ProductID (part of the composite key)
   • ProductName
   • Quantity

Now we have two tables:

Orders:

• OrderID (Primary Key)
• CustomerName
• CustomerAddress

OrderDetails:

• OrderID (Foreign Key)
• ProductID (Primary Key)
• ProductName
• Quantity

By splitting the original table this way, we have ensured that all non-key attributes in the Orders and OrderDetails tables fully depend on the primary key. This means both tables are now in the second normal form.

Applying the second normal form helps to avoid update anomalies and ensures a consistent data structure.

The first normal form (1NF) is a rule in relational database design that ensures a table inside a database has a specific structure. This rule helps to avoid redundancy and maintain data integrity. The requirements of the first normal form are as follows:

1. Atomic Values: Each attribute (column) in a table must contain atomic (indivisible) values. This means each value in a column must be a single value, not a list or set of values.
2. Unique Column Names: Each column in a table must have a unique name to avoid confusion.
3. Unique Row Identifiability: Each row in the table must be uniquely identifiable. This is usually achieved through a primary key, ensuring that no two rows have identical values in all columns.
4. Consistent Column Order: The order of columns should be fixed and unambiguous.

Here is an example of a table that is not in the first normal form:

In this table, the "PhoneNumbers" column contains multiple values per row, which violates the first normal form.

To bring this table into the first normal form, you would restructure it so that each phone number has its own row:

By restructuring the table this way, it now meets the conditions of the first normal form, as each cell contains atomic values.

In database theory, normal forms are a series of guidelines used to standardize the structure of relational database schemas to minimize redundancy and avoid anomalies in data operations. The most important normal forms range from the first to the fifth normal form (1NF to 5NF) and the Boyce-Codd Normal Form (BCNF). Here is an overview:

1. First Normal Form (1NF):

   • Definition: A relation schema is in 1NF if all attribute values are atomic, meaning each attribute contains only indivisible values.
   • Goal: Eliminate repeating groups and ensure that the data is in tabular form.

2. Second Normal Form (2NF):

   • Definition: A relation schema is in 2NF if it is in 1NF and every non-key attribute is fully functionally dependent on the entire primary key.
   • Goal: Eliminate partial dependencies, where a non-key attribute depends on part of a composite primary key.
3. Third Normal Form (3NF):
   • Definition: A relation schema is in 3NF if it is in 2NF and no non-key attribute is transitively dependent on the primary key.
   • Goal: Eliminate transitive dependencies to ensure non-key attributes depend only on the primary key.
4. Boyce-Codd Normal Form (BCNF):
   • Definition: A relation schema is in BCNF if it is in 3NF and every non-trivial functional dependency $X\to Y$ (where $Y$ is not a subset of $X$) implies that $X$ is a superkey.
   • Goal: A stricter form of 3NF to avoid all dependency anomalies.
5. Fourth Normal Form (4NF):
   • Definition: A relation schema is in 4NF if it is in BCNF and has no non-trivial multi-valued dependencies.
   • Goal: Eliminate multi-valued dependencies where an attribute depends on another attribute and also has multiple independent values.
6. Fifth Normal Form (5NF):

• • Definition: A relation schema is in 5NF if it is in 4NF and every join dependency in the schema is implied by the candidate keys.
  • Goal: Eliminate join dependencies to ensure relations can be decomposed and recombined without information loss.

These normal forms aim to optimize data structures, minimize redundancy, and ensure data integrity. While not all normal forms are applied in practice to the highest level, they provide a theoretical foundation for designing robust and efficient databases.