Normalization is an important concept in database design, as it helps to organize the data in a database in a way that reduces redundancy, inconsistency and introduces dependency. The process is used to minimize this problems by organizing the data into smaller, more cohesive units. By following the principles of normalization, it is possible to design a database that is more efficient, accurate, and easier to maintain.
Redundancy refers to the duplication of data within a database. For example, if a database stores customer information and the same customer's name and address are stored in multiple tables or records, there is data redundancy.
Data redundancy can be problematic because it can lead to inconsistencies and errors in the data. For example, if a customer's name is spelled differently in different records, it can be difficult to accurately retrieve and use the data. Additionally, redundant data can take up unnecessary space in the database and make it more difficult to update or modify the data.
Dependency refers to the relationship between data in a database. For example, if a database stores information about employees and their departments, there is a dependency between the employee data and the department data. If an employee is moved to a different department, the department data for that employee must also be updated in order to maintain the accuracy of the database.
Dependencies can be problematic because they can make it more difficult to modify or delete data. For example, if an employee is deleted from the database, any data that depends on that employee's information must also be deleted or modified. This can be time-consuming and error-prone if there are many dependencies.
Data inconsistency can occur when the same piece of information is stored in multiple places within a database, and the values are different. For example, if a customer's name is spelled differently in different records, it can be difficult to accurately retrieve and use the data. Inconsistencies in data can also occur when data is updated in one place but not in others, leading to a lack of synchronization.
The normalization follows this steps which build up on each other and make up rules, which help to design a more robust database. The normal forms define what condition needs to be satisfied to complete the normalication for thsi step.
To satisfy First normal form, each column of a table must have a single value. Columns which contain sets of values or nested records are not allowed.
This may introduce redundancy at first, but because the fields are now in there smallest form, they can be defined as a primitiv data type and make the data more consistent
If a table has a single column primary key, it automatically satisfies 2NF, but if a table has a multi-column or composite key then it may not satisfy 2NF. The second Part of the rule is obsolete, when every non primary key attribute is dependent on all parts of the composit primary key.
This forces the databases designer to extract data which does not belong to every part of the composit key and makes the database more consistent.
The database is in the 3 normal form, when there are no transitive dependencies in the table (i.e., no non-key field depends on another non-key field).
Introduce higher levels of normalization, such as 4NF and 5NF. Discuss the benefits of higher levels of normalization and when they may be necessary. Provide examples of how to apply higher levels of normalization to a database
Summarize the importance of normalization in database design. Emphasize the benefits of normalization in terms of data efficiency and integrity. Encourage the audience to consider the principles of normalization when designing their own databases.