The main difference between data integrity and data redundancy is that data integrity is the process of ensuring that the data is accurate and consistent over its whole life cycle, while data redundancy is a condition that can cause the same piece of data to be stored in multiple places of a database or a storage device.
Generally, data is important to individuals as well as for business organizations. Therefore, it is necessary to store data to make valuable decisions. Overall, data integrity and data redundancy are two terms associated with data.
Key Areas Covered
1. What is Data Integrity
-Definition, Functionality
2. What is Data Redundancy
-Definition, Functionality
3. Difference Between Data Integrity and Data Redundancy
-Comparison of key differences
Key Terms
Data Accuracy, Data Integrity, Data Redundancy
What is Data Integrity
Data integrity is the process of ensuring the accuracy and consistency of data over its entire life cycle. Data integrity helps to avoid unintentional changes to information. Moreover, data validation helps to maintain data integrity.
Data can change due to various reasons. There can be changes during storage, retrieval and processing operation. Furthermore, malware, hardware failures and human errors can also make changes to data. If any change occurs due to unauthorized access, it can be a failure of data security. Data integrity prevents data from getting changed by the above situations. Therefore, it is extremely important to maintain data integrity. Otherwise, it can affect business-critical applications, and it may also harm human life.
What is Data Redundancy
Data redundancy is the replication of data. In other words, there are copies of the actual data at multiple places. It is a common issue in computer storage and database systems. For example, assume that a certain value in the field of a table is repeated in the same table again or in another table. It is possible to use normalization to avoid data redundancy of a database.
Overall, data redundancy can cause multiple issues. Firstly, it can increase the size of the database or any other storage. It can also cause data inconsistency. Another issue is that it can minimize the efficiency of the database or any other storage device. Finally, it can cause data corruption.
Difference Between Data Integrity and Data Redundancy
Definition
Data integrity is the maintenance and assurance of the accuracy and consistency of data over its entire life-cycle. In contrast, data redundancy is the repetition or superfluity of data. Thus, this is the main difference between data integrity and data redundancy.
Usage
While data integrity helps to improve data consistency, data redundancy reduces data consistency.
Impact
Moreover, data integrity has a positive impact, while data redundancy has a negative impact. That is another difference between data integrity and data redundancy.
Conclusion
In brief, data integrity and data redundancy are two terms that are associated with storing data in computer systems or any other storage device. The main difference between data integrity and data redundancy is that data integrity is the process of ensuring that the data is accurate and consistent over its whole life cycle while data redundancy is a condition that can cause the same piece of data to be stored in multiple places of a database or a storage device.
References:
1.“Data Integrity.” Wikipedia, Wikimedia Foundation, 1 Aug. 2019, Available here.
2.“Data Redundancy.” Wikipedia, Wikimedia Foundation, 2 May 2019, Available here.
Image Courtesy:
1.”Types of data” By João Batista Neto – Data types – pt br.svg (CC BY 3.0) via Commons Wikimedia
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