DATA INTEGRITY
Data integrity is a crucial area of database security and is the overall maintenance and assurance of data consistency, accuracy and completeness. It is also referred to as the safety and security of data according to compliance regulations (Talend, 2021). According to Brook (2020), data integrity is the accuracy and validity of data over its lifecycle. Data integrity ensures that data remains in its constant unaltered nature when copied or transferred. However, data integrity differs from data security in that data security is the protection of data from attackers and violations (Brook, 2020).
The organization Talend in ‘What is data integrity and why is it important?’ describes data integrity vividly and its vitality in the database systems as well as our lives. Furthermore, the source describes the various types of data integrity in detail and their constraints and rules. Talend clarifies on what data integrity is not and differentiates data integrity and data security as the two concepts are often confused as one. Data integrity compliance with protection regulations as well as data integrity risks are also discussed and how to get started with data integrity. Talend gives all the necessary details regarding data integrity on all fronts and chapters.
Chris Brook on ‘What is Data Integrity? Definitions, Best Practices & More’ follows a more similar approach to data integrity as Talend. Brook makes a brief description of data integrity, how it is violated and the importance od data integrity. He further adds data integrity as a state and as a process and distinguishes the two features. Brook defines a case for data integrity and highlights in details the application of data integrity to databases by defining the various types of data integrity. Finally, the article distinguishes data integrity from data security by highlighting the similarities and differences of the two. Chris Brook gives insight in example form on data integrity.
The paper seeks to discuss data integrity as an area of database security in full detail. While data integrity constitutes the validity and consistency of data, data security refers to the protection of data hence can be described as a means to maintain data integrity. The importance of data integrity is very crucial and is limitless but the paper helps outline the major importance of maintaining data integrity and also how data integrity is compromised in various situations such as in organizations and local databases such as human error, viruses and cyber threats, transfer errors.
There are four types of data integrity namely entity integrity which utilizes the use of primary keys to avoid data replication. Referential integrity entails rules on the use of foreign keys in data manipulation. Domain integrity that ensures accuracy of every data contained in a domain and user-defined integrity which contains rules created by users to fit their needs (Talend, 2021). These types of domain are further discussed highlighting their features, examples and use.
Data integrity is differentiated to what it isn’t such as data security. Data security is the protection of data against corruption while data integrity focuses on keeping data accurate and consistent. Data security can be considered a measure employed to maintain data integrity (Brook, 2020). The differences and similarities of the two concepts are clearly highlighted in the paper to create a clear understanding of what data integrity is and isn’t. The risks associated with data integrity such as human and transfer error, cyber threats and compromised hardware are also laid out as well as the means to minimize and/or eliminate the data integrity risks.
