Handling Data Redundancy in Databases

What is Data Redundancy?
Data redundancy is data stored in more than one location in one database. Data redundancy can occur intentionally or unintentionally. Redundant data occurs intentionally, usually by making a copy of data so that the data is not only available at one location, so if data at location a is lost, the data is still available at location b. Meanwhile, redundant data that occurs accidentally usually occurs due to design or structural errors in the database and can also occur due to errors when entering data. However, redundant data rarely occurs on purpose because it will cause several problems, which will be discussed below.

Problems that will arise from data redundancy
The following are some problems that will arise as a result of data redundancy:

• The Database Size Becomes Larger
  Due to data redundancy, the size of the database will increase. So, larger storage space is needed. The costs incurred will also be more significant with the need for larger storage space.
• Databases are Becoming More Complex
  The complexity caused by data redundancy results in difficulties in managing databases, changing databases, and searching for and retrieving redundant data. When data redundancy occurs, it can cause duplication of tables and columns, making the data difficult to read and understand.
• Risk of Data Errors
  The same data in different locations must always be maintained consistently to avoid data errors. So, if there is a change in data in one area, data in other places also needs to be changed; if it is not, it can be confusing because there are differences in data, and we need to know which data is accurate.

Overcoming Data Redundancy
Here are several ways to overcome data redundancy:

• Using Master Data
  Data master is that data becomes the main source of data in the organization. By using master data, data is stored in only one location. However, the main benefit of using master data is not to reduce data redundancy. The benefit is that if there is redundant data that you want to change in one master data, you only need to change one data.
• Database Normalization
  Normalization is arranging data in a database to make it more efficient and effective. It reduces data redundancy by breaking data into several interrelated tables. That way, the data displayed will be easier to read and understand, and it will be easy to change information in the data.
• Delete Unused Data
  If data will no longer be used in the future, it should be deleted from the database. This can reduce data redundancy and optimize database performance.
• Proper Database Design
  By designing the correct database, you can reduce data redundancy. When creating a database, you must focus on details to avoid storing the same data in two or more tables.

References
-Putri, F. (2022, October 8). Data Preparation – Fani Putri – medium. Medium. https://medium.com/@faniptrs/istilah-istilah-yang-perlu-kamu-ketahui-sebelum-terjun-ke-data-analytics-c9d719f7dd88
-Keinsinyuran. (2022, May 17). Data redundancy adalah: pengertian, maksud, contoh + penjelasannya! https://www.keinsinyuran.com/kamus/data-redundancy/
-Griyasis. (n.d.). Griyasis. 5 Cara Mengatasi Redundansi Data Yang Benar | Griyasis. https://www.griyasis.com/5-cara-mengatasi-redundansi-data-yang-benar