Database normalization is the process of restructuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity.
What are the three steps in normalizing data? What are the three goals of normalization?
Why is normalization needed in the design of the database?
Research and find a specific example of unnormalized data (or come up with your own example). Share why this data is considered unnormalized and discuss the problems with the data in its current form in context with what we hope to accomplish when we normalize the design.
Full Answer Section
The three goals of normalization are:
- To reduce data redundancy: This is done by storing each piece of data in one place only.
- To improve data integrity: This is done by ensuring that the data in the database is consistent and accurate.
- To make the database easier to use: This is done by making the data easier to access and update.
Why is normalization needed in the design of the database?
Normalization is needed in the design of the database because it helps to improve the efficiency, reliability, and flexibility of the database.
- Efficiency: Normalization can help to improve the efficiency of the database by reducing the amount of data that needs to be stored. This can improve the performance of the database and reduce the amount of storage space that is required.
- Reliability: Normalization can help to improve the reliability of the database by reducing the risk of errors. This is because normalization helps to ensure that the data in the database is consistent and accurate.
- Flexibility: Normalization can help to improve the flexibility of the database by making it easier to add new data or to change the existing data. This is because normalization helps to ensure that the data in the database is stored in a logical and consistent manner.
Unnormalized data is data that is not stored in a normalized form. This can lead to a number of problems, including:
- Data redundancy: This occurs when the same data is stored in multiple places in the database. This can waste storage space and can make it difficult to keep the data consistent.
- Data anomalies: This occurs when the data in the database is inconsistent or inaccurate. This can lead to errors in the database and can make it difficult to use the data.
- Difficult to update: The data in an unnormalized database can be difficult to update. This is because changes to the data may require changes to multiple tables in the database.
Example of unnormalized data:
An example of unnormalized data is a table that stores information about customers and their orders. The table might include the customer's name, address, and phone number, as well as the order number, date, and product ordered.
This table is unnormalized because the customer's name, address, and phone number are stored multiple times, once for each order. This wastes storage space and can make it difficult to keep the data consistent.
To normalize this data, we would need to create separate tables for the customer information and the order information. This would ensure that the customer information is only stored once in the database and that the order information is only stored once in the database.
By normalizing the data, we would improve the efficiency, reliability, and flexibility of the database.