Data Analytics Glossary

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What is Redundancy?

Data redundancy is the repetition of some data. Data redundancy occurs when the same piece of data is stored in two or more separate places for example tables’ rows or columns. Suppose a user creates a database to store sales records, and in the records for each sale, they enter the customer address. Yet, you have multiple sales to the same customer so the same address is entered multiple times. The address that is repeatedly entered is redundant data.

How does Data Redundancy occur?

Data redundancy can be designed; for example, suppose you want to back up your company’s data nightly. This creates a redundancy. Data redundancy can also occur by mistake. For example, the database designer who created a system with a new record for each sale may not have realized that his design caused the same address to be entered repeatedly. You may also end up with redundant data when you store the same information in multiple systems.


If you are designing a system for a university. There’s a requirement to store the addresses of people in the system as well and you have separated faculty from admin staff and storing them in two tables. Now you are also storing information about student’s addresses as well. When you will choose cities for all these different types of people, you may end up adding the same city to hundreds of students, teachers, and admin staff. The result is going to be the same city name in different parts of the database. This is called redundant data.

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