Normalization

Normalization is the process of organizing data in a database to eliminate redundancy and improve data integrity. It involves breaking down a database into multiple tables and establishing relationships between them.

The main goal of normalization is to reduce data redundancy by minimizing the amount of duplicate data in the database. By doing so, normalization helps to prevent data inconsistencies and anomalies, such as update anomalies, insert anomalies, and delete anomalies.

Normalization is achieved through a set of guidelines called normal forms. The most commonly used normal forms are:

• First Normal Form (1NF)
• Second Normal Form (2NF)
• Third Normal Form (3NF)
• Boyce-Codd Normal Form (BCNF)

Each normal form has specific rules and requirements that must be met to ensure the database is properly normalized.

Let's take a look at an example of normalizing data using Python:

1def normalize_data(data):
2    normalized_data = {}
3    for record in data:
4        for key in record:
5            if key not in normalized_data:
6                normalized_data[key] = []
7        normalized_data[key].append(record[key])
8    return normalized_data
9
10data = [
11    {"id": 1, "name": "John", "age": 25, "city": "New York"},
12    {"id": 2, "name": "Jane", "age": 30, "city": "San Francisco"},
13    {"id": 3, "name": "Mike", "age": 35, "city": "Chicago"}
14]
15
16normalized_data = normalize_data(data)
17print(normalized_data)

In this example, we have a list of dictionaries representing records. The normalize_data function takes this data and normalizes it by converting it into a dictionary of lists, where each key represents a column name and the corresponding list contains the values for that column.

Normalization is an important process in database design as it helps to optimize storage space, improve performance, and ensure data integrity.

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if __name__ == "__main__":

  # Python logic here

  def normalize_data(data):

    normalized_data = {}

    for record in data:

      for key in record:

        if key not in normalized_data:

          normalized_data[key] = []

        normalized_data[key].append(record[key])

    return normalized_data

​

  data = [

    {"id": 1, "name": "John", "age": 25, "city": "New York"},

    {"id": 2, "name": "Jane", "age": 30, "city": "San Francisco"},

    {"id": 3, "name": "Mike", "age": 35, "city": "Chicago"}

  ]

​

  normalized_data = normalize_data(data)

  print(normalized_data)