Advantages And Disadvantages Of Database Normalization?

The advantages of database normalisation are that it makes the process of changing the data in a table for a lot if its components easier, because normalising a database enables the user to create relationship strands between the pieces of information. Like pieces of information will appear in a separate, smaller table when a database is normalised. This is also an advantage of normalisation because it means that you can easily find like pieces of information within a table.
Normalisation helps to reduce redundancy rates within companies because when a database is normalised, it pulls out all the abnormal factors to do with workers that do not fit in to the general consensus of the company. This can help when recruiting personnel, because it means that only the suitable candidates go through to interview in the first place, lessening the strain on company resources but at the same time making sure that the company gets the very best workers.
Normalisation can also be handy in finding anomalies within data. For example, if an employee recently changed addresses, but only one of the databases that they are on is updated, normalisation would recognise this as abnormal and flag the issue up to human resources. The issue can then be rectified quickly and effectively by the human resources team simply updating the other databases.
Normalisation also has its disadvantages, though. It can be very difficult and time consuming to input the relevant formulas to get the database to function properly, but if you are competent with computing this should not be too much of an issue.
Normalisation is used in almost all large company databases because it is the easiest way to organise large scores of data. It has a lot more advantages than disadvantages for the companies that use it.

Advantages

1) Avoids data modification (INSERT/DELETE/UPDATE) anomalies as each data item lives in One place

2) Greater flexibility in getting the expected data in atomic granular

3) Normalization is conceptually cleaner and easier to maintain and change as your needs change

4) Fewer null values and less opportunity for inconsistency

5) A better handle on database security

6) Increased storage efficiency

7) The normalization process helps maximize the use of clustered indexes, which is the most powerful and useful type of index available. As more data is separated into multiple
tables because of normalization, the more clustered indexes become available to help
speed up data access.

Disadvantages

1) Requires much more CPU, memory, and I/O to process thus normalized data gives reduced database performance

2) Requires more joins to get the desired result. A poorly-written query can bring the database down

3) Maintenance overhead. The higher the level of normalization, the greater the number of tables in the database.

Advantages
•Avoids data modification (INSERT/DELETE/UPDATE) anomalies as each data item lives in One place
•Greater flexibility in getting the expected data in atomic granular
•Normalization is conceptually cleaner and easier to maintain and change as your needs change
•Fewer null values and less opportunity for inconsistency
•A better handle on database security
•Increased storage efficiency
•The normalization process helps maximize the use of clustered indexes, which is the most powerful and useful type of index available. As more data is separated into multiple tables because of normalization, the more clustered indexes become available to help speed up data access
Disadvantages
•Requires much more CPU, memory, and I/O to process thus normalized data gives reduced database performance
•Requires more joins to get the desired result. A poorly-written query can bring the database down
•Maintenance overhead. The higher the level of normalization, the greater the number of tables in the database.

First normal form with example