Every day data is generated and stored globally which exposes its integrity to risk. Data, in essence, mean facts and statistics which are compiled for the purposes of analysis or making references. Further, data can be defined as the things assumed to be facts which in one way or the other form the basis for reasoning, decision making, and calculations. We actually should care if the data therein is incorrect or its overall quality is poor. In this manner, data integrity is the quality of data. Additionally, data integrity can be interpreted as a process of maintaining as well as assuring the consistency and accuracy of the data through its life cycle. This is a critical aspect for systems which store, process or retrieve the data. Keen consideration should be put on the design, implementation, and usage of data of any kind to avoid issues such as data integrity breach.
Data integrity breaches would mean issues to deal with compromise in data retrieval, implementation, and even usage. We can derive from Lloyd’s of London the knowledge that the financial world spends as much as four hundred billion dollars to mitigate against cyber breaches. This much goes into remediation and preventative activities. Other sectors and organizations such as education, military, utilities, municipalities, and medicine as well hold importance on data integrity as core to their functions. Primarily, data integrity should not be confused with data security because data integrity informs decision making and such while data security is the protection of the same so that it does not fall on unintended hands.
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Basically, all forms of changes on the data due to storage, retrieval or processing activities, as well as malicious intent, human error or hardware failure constitute to compromises on data integrity. Depending on the type of data therein, such compromises can cost the involved organization a great deal (Hao, Zhong, & Yu, 2011). It can begin as a pixel of an image presenting a different color from the originally recorded and culminate into other serious issues such as loss of business critical database or even loss of human life.
The consequences of an altered, compromised or breached data are dire. In the health care context for example breaches or alterations on patient records could result in risks in the lives of the patients. Furthermore, erratic or unintended changes on the diagnoses, medication records, and medical history could be disastrous. Additionally, public companies, financial institutions, and even small business rely so much on data integrity. Unauthorized changes in the data therein could lead to significant problems. According to Hao, Zhong, & Yu (2011), this is even worse when the data in context forms part of fillings with a regulatory body or a report to shareholders.
Thinking about the human resource especially in the military, the impact of alterations and compromises on data and systems could in a huge way affect the reorganizations, payroll updates, talent movement, and onboarding among other critical issues. The same can affect protocols and in the context of war, there can be a serious loss of soldiers’ lives and the possibility of winning the war is minimal. In education as well, compromised data might result in inaccurate decision making in the context of student performance and even the most appropriate deliverables to make the education system better. The impact can be felt generations after generations. Therefore there is a need to ensure the highest levels of data integrity if at all the same could be used in decision making or any other purposes.
Reference
Hao, Z., Zhong, S., & Yu, N. (2011). A privacy-preserving remote data integrity checking protocol with data dynamics and public verifiability. IEEE Transactions on Knowledge and Data Engineering , 23 (9), 1432-1437.
