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Database normalization reduces redundant information in relational databases to minimize data anomalies. It breaks down large tables, improves data relationships, and isolates information to make it easier to change data. Normalization should be used periodically to keep the database up-to-date and free from unexpected problems. Anomalies occur from refusal or forgetfulness to normalize the database and can render information useless. Scheduling database normalization about once a week is usually best.
Database normalization is used in a database management system (DBMS), especially with relational databases, to reduce redundant information and thus minimize data anomalies. Anomalies can arise from poorly grouped or redundant information and can cause a variety of effects, such as incorrect data entry or deletion of an entire group of data. By using database normalization, these anomalies are avoided and memory is usually freed up so that the database can run more efficiently. The normalization functions should be used periodically, about once a week, to keep the database up-to-date and free from unexpected problems.
No one creates a relational database to have redundant data on purpose, but this usually happens despite the best efforts of the database designer. For example, with an employee database, one employee might be listed across multiple tables. When large-scale redundancy occurs, glitches occur. Database administrators typically cannot detect all redundant data, so database normalization is the best way to correct this problem.
The first task of database normalization is to delete or move repeating information. If the information is not needed, it will be deleted from the database. For data needed in other tables, normalization tries to make better relational tables. Normalization functions will break down large tables, fix and improve data relationships, and isolate information to make it easier for you to change data in your database. By subtracting the repeating data, memory is usually freed up, which allows the database to run smoother and faster.
Anomalies occur from refusal or forgetfulness to normalize the database and can render information useless. An update anomaly occurs when someone updates the data, but instead of changing the target data, the database will create a new, highly redundant record. With an insert anomaly, a record is added to the database, but nothing can be added below the new record. Deletion anomalies will randomly delete a record. These are just some common anomalies that occur if the database is not normalized.
There is no fixed standard that tells an administrator when to use normalization features to ensure database effectiveness. Scheduling database normalization about once a week is usually best because it prevents any new information added during the week from glitching. Smaller databases can probably be normalized once a month, and very large databases should be run twice a week because larger amounts of data mean a greater chance of anomalies. However, there is no standard, so the database administrator usually chooses a schedule that he thinks is best for the database.
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