Data redundancy is the repetitive storage of the same data in multiple places within a database OR duplicate storage of the same data in more than one databases.
Data redundancy can happen consciously for backup or data security purposes. Sometimes it may happen accidentally due to poor database design or inefficient software design.
Now, you got the point that the data repetition leads to data redundancy.
What is data repetition?
Data repetition or repetitive storage of data means a single piece of data is stored more than one time. It can occur by creating two or more fields for one data in a database. Or by storing one field of data in multiple databases.
Whatever the repetition type, when the same data is repeated, it simply results in data redundancy.
What is Data Redundancy in DBMS – database management system?
In database management, data redundancy refers to the duplication of data in a database. This means that the same piece of data is stored in multiple places within the database.
Data redundancy can have both advantages and disadvantages.
The main advantage of data redundancy is that it can improve the reliability and availability of the data, since multiple copies of the data are stored. If one copy of the data is lost or becomes unavailable, the other copies can be used to access the data.
However, data redundancy can also have some disadvantages.
One of the main disadvantages is that it can lead to data inconsistencies, where different copies of the data are not the same.
This can be a problem if the data is updated, as the different copies of the data will not be in sync with each other. This can make it difficult to know which copy of the data is correct.
Overall, while data redundancy can be useful in some situations, it is important to carefully consider the trade-offs before implementing it.
What are the some real world examples of data redundancy?
Assume, you are analyzing a database of an e-commerce organization. At that point some real life examples of data redundancy could be:
- Storing the same customer information in multiple databases or servers. Examples include a customer’s name, address, and contact information.
- Maintaining multiple copies of the same product information, such as product descriptions and prices.
- Keeping multiple copies of the same financial records, such as invoices and receipts, in different locations.
- Duplicating the same data in different formats. Such as storing an invoice both in text and images or pdf format.
- Storing the same data in different languages or translations. Example: storing a product’s description in different languages.
- Keeping multiple copies of the same data for backup purposes. Like storing the same data on multiple servers or storage devices.
Disadvantages of data redundancy
Here are some disadvantages you are going to face:
- Data inconsistency
- Inefficient Database
- Superfluous or excessive data
- Complexity in data processing
- Risk of corrupted database
- Unnecessary larger database
- Increase in cost of data storage
- Difficult to backup and recovery
- Reduced flexibility
If the same data is stored in multiple places, it is possible for inconsistencies to arise if the data is updated in one place but not in others. This can lead to confusion and errors.
Storing and managing redundant data can make certain database operations slower and less efficient.
Superfluous or excessive data
Redundant data makes a database superfluous, resulting compromise the integrity of the data and make it unreliable. Besides it increases storage requirement.
Complexity in data processing
Redundant data can make a database more complex and difficult to manage, as it may require additional steps to ensure that the data is consistent and accurate. It makes difficult to analyze and report based on the data.
Risk of corrupted database
Data security risks: Storing the same data in multiple places can increase the risk of unauthorized access or modification of the data.
Increase in cost of data storage
Storing and managing redundant data requires additional resources, such as storage space and processing power. Which increases maintenance cost of database.
Difficult to backup and recovery
Redundant data make it more difficult to back up and restore a database. It may require additional steps to ensure that all copies of the data are included in the backup.
Data redundancy reduces the flexibility of the database. You may need to change the structure of a database or shift to a newer technology in some point of time. To implement this you will face a hard time and may require additional steps to ensure that the data is still consistent and accurate.
How to avoid data redundancy in Database Management System
There are several ways to avoid data redundancy in a database management system, including:
Normalization of database
This process involves organizing the data in a database into multiple related tables, and ensuring that each table contains only the data that is relevant to the specific purpose of that table. This can help reduce redundancy by ensuring that the same data is not repeated in multiple tables.
Primary and foreign keys
In a database, a primary key is a unique identifier for each record in a table, while a foreign key is a reference to the primary key of another table. By using primary and foreign keys, a database can be designed to ensure that data is not repeated unnecessarily.
Use of stored procedures
Stored procedures are pre-defined pieces of code that can be used to perform specific tasks within a database. By using stored procedures, it is possible to ensure that the same data is not entered multiple times, and to avoid inconsistencies in the data.
Use of constraints
Constraints are rules that are applied to the data in a database to ensure that it is valid and consistent. For example, a constraint could be used to ensure that no two records in a table have the same primary key value. By using constraints, it is possible to avoid data redundancy and ensure the integrity of the data in a database.