Data protection reliability is the method that guarantees data is accurate, complete and secure throughout its entire lifecycle, from the moment of creation until deletion or archival. This includes safeguarding against unauthorised data access, corruption, and errors by utilizing robust security measures, audits and checksum validations. Reliability of data is essential in enabling confident and informed decision-making, empowering organizations to leverage data to improve business performance.
The accuracy of data can be compromised by a range of factors, such as:
Data Source Credibility. The trustworthiness of a dataset and its credibility are greatly dependent on its provenance. Credible sources have a history of producing reliable information and are verified through peer reviews, expert validations, or adherence to industry standards.
Human errors: Data like this entry and recording mistakes can introduce errors into the data, which reduces its reliability. Standardized processes and training are key to avoiding these mistakes.
Backup and storage: A backup plan, like the 3-2-1 method (3 copies on two devices local and one offsite) helps to prevent data loss due to natural disasters or hardware malfunctions. Physical integrity is a different aspect to consider. Businesses that make use of multiple technology vendors must ensure that the physical integrity of all their data systems to be secured and maintained.
Reliability of Data is a thorny issue the most important thing being that a business is using trusted and reliable data to inform decisions and generate value. To do this, businesses need to create an environment of trust and confidence in data and ensure that their processes are designed to yield reliable results. This means implementing standard methods, educating personnel who collect data, and offering reliable software.