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What Does Data Redundancy Mean in Database Design?

What Does Data Redundancy Mean in Database Design?

Among the several confusing terms in the world of computer science is what is known as data redundancy. In this Techspirited article, we try and clarify the concepts behind this terminology and its implications in database design.
Satyajeet Vispute
Did You Know?
In some instances, data redundancy is a desirable trait. For example, in personal computer systems, duplicating data helps in the process of data restoration in the event of data loss or corruption.
To understand what data redundancy means, let's first understand what a redundant object is. A redundant object, by definition, is one which isn't required or necessary. Data redundancy therefore refers to data present in the database that is redundant, and hence, not required for the functioning of the system.

Usually, data redundancy occurs in database systems when two or more tables have the same field repeated in them. The presence of duplicate data almost always has undesirable effects. For example, data redundancy in database systems can increase the database response time to queries and return results that are either not helpful, expected, or even completely wrong.

Therefore, it is one of the core functions of data management to identify duplicate data and to logically get rid of it while making sure database integrity is maintained. In the following sections, we look at how data redundancy affects different databases, and how it can be avoided.

Data Redundancy in Database Design
Several types of database systems are available for different applications. Though the improved logic used in the more modern database designs significantly reduces the chances of data redundancy, the fact remains that no system is truly immune to it. The only difference is that some systems are more prone to data redundancy than others.

Flat software programs such as spreadsheets, which rely on manual data entry by the user, are most susceptible to data duplication. This is mostly because of human error and has the adverse effect of generating complications at the time of data retrieval.

In the other type of databases, i.e., the relational databases such as the sales contacts, often, checks are kept in place to minimize the chances of unintentional data duplication. For instance, if two different contact files having the same number and the same company address are found in such a database, it will either automatically get rid of one or notify the user about the error.

However, even with these checks in place, chances are that data redundancy would take place in relational databases as well. It therefore becomes vital that special software programs be used for verification and cleanup of the data present within a database.

Problems Resulting from Data Redundancy
There are several problems associated with data redundancy. At the lowest level, redundant data only causes a database to contain unnecessary garbage information which doesn't impede its ability of locating the relevant data as and when needed.

At the highest level of data redundancy, however, duplicate data can completely clog up a database, preventing it from performing essential search functions. This can lead to inconsistencies in the database system's performance.

An example of this is a customer database in a shopping store, which is completely clogged up with non-essential redundant data. The generation of a mailing label from the information in such a database would result in the creation of several different duplicate fields. Thus, it is essential to sort and dispose the duplicate fields before attempting to generate the labels.

Data redundancy can also affect data integrity within a database system. When updates are made to one of the entries, it becomes essential that the same updates are made to the rest of the duplicate ones; failing which, the system will experience data anomalies.

How to Avoid Data Redundancy in a Database
To avoid data redundancy, a procedure for monitoring and correction of instances of data duplication has to be employed. Thanks to advances in modern data management systems, this can be achieved relatively easily.

Many systems will flag the instances of redundant data and notify the user about its existence. This allows the user to review the entries and decide whether to delete or keep them.

For large databases, smart software solutions exist that scan the database for duplications, and automatically decide whether or nor to get rid of the redundant entries.

Thus, data redundancy in database systems is the unintentional duplication of the data fields that, in most cases, adversely affects its performance. It is an undesirable occurrence which modern-day database design constantly seeks to eliminate.