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Why Is Data Integrity Important

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Data integrity refers to the accuracy, consistency (validity) of data over its lifecycle. Compromised data is of little use to enterprises, not to mention the dangers presented by sensitive data loss. Consequently, data integrity is one of the most critical elements in any system Subashini & Kavitha, 2010) and it is a core focus of many enterprise security solutions.
Data integrity defines the quality of information, which guarantees the data exist, is accurate, complete, and has a whole structure. Data integrity is preserved only if and when the data is satisfying all the business requirements and important rules and regulations. These requirements and rules might be how data is processed, linked, validity of details and content, etc. According …show more content…

Data integrity as a state defines a data set that is both accurate and valid. Furthermore, data integrity as a process, describes measures used to ensure validity and accuracy of a data set or all data contained in a database or other construct. For instance, error detection and data validation methods may be referred to as data integrity processes.
Maintaining data integrity is important and key to the companies for several reasons as data integrity ensures the accuracy of the information recoverability, searching ability, traceability connectivity and analysis. Protecting the validity and accuracy of data also increases stability, performance and drive decision-making considering the data can be maintained and reused when needed.
Data integrity drives enterprise decision-making, but it may undergo a variety of processes and organizing changes to transform from raw form to usable formats as needed and practical for reporting, analysis and facilitating the users’ decisions. Therefore, data integrity is key and a top priority for all …show more content…

However, only some of the abovementioned compromises may be adequately prevented through data security. Consequently, data backup, duplication and storage become critical for ensuring data integrity. Other data integrity security best practices include input validation to prevent the entering of invalid data, error detection/data validation to identify and check errors in data transmission, and security measures such as data loss prevention, access control, data encryption, and more.
Most of the business debates and concerns regarding cyber threats have focused on the confidentiality, accessibility and availability of information. In the future, it is expected more cyber operations to change or manipulate electronic information in order to compromise its integrity in terms of accuracy and reliability, instead of deleting it or disrupting access to it. When corporate executives, investors, or other stakeholders cannot trust the information they are receiving, their decision-making will be impaired.
Successful cyber operations targeting the integrity of information would need to overcome any restrictions, data checks and balances designed to prevent the manipulation of the

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