Normalization and Data Redundancy

Data Redundancy and Database Normalization

Data redundancy in computer buses, auxiliary storages, and main memory is the presence of data that is added to the proper data and permits error repair in the transmitted or stored data. Notably, the saved data can be a complete copy of the original data and its fragments, allowing for the reconstruction of damaged or deleted data as well as error detection. Data redundancy occurs in database management systems when values are repeated in one or more fields or records within a table needlessly (Bowers, 2013).

Database Normalization

On the other hand, database normalization refers to the process of organizing the relations and attributes of a relational database to minimize redundancy of data with the aim of improving the integrity of the data. If the databases are not normalized, a significant amount of data is duplicated within the system, and the data fails to be grouped logically. Also, the denormalized database does not have greater flexibility and also brings forth the issue of failing to handle the security of the database better.

Data Warehousing and Normalization

Concerning data warehousing, data normalization is critical since it helps to address the problems of insertion, deletion, and update anomalies (Fleming & VonHalle, 2016). Insertion anomalies refer to cases where it is impossible to insert certain types of data into the system. Deletion anomalies apply to a situation where intended data is lost without the wish of the user of the database. Finally, update anomalies refer to inconsistencies that arise as a result of updating the value of a column in the database (Fleming & VonHalle, 2016).

Normalization is crucial for efficient database design and development since it avoids the anomalies as a result of each data item residing in a single place. Also, the process leads to greater flexibility and fewer cases of inconsistencies within the database, and it also allows increased storage efficiency.

References

Bowers, D. (2013). From data to database. London: Chapman & Hall.

Fleming, C., & VonHalle, B. (2016). Handbook of relational database design. Reading, Mass. [u.a.]: Addison-Wesley Publ.