Reliability of data protection is the process of making sure that data is accurate complete, secure, and safe throughout its entire lifecycle, from creation until archival or deletion. This means securing against unauthorised access as well as data corruption and mistakes by taking rigorous security measures, frequent audits, and checksum validations. Reliability of data is vital to enabling confident and informed decision-making, which allows companies to use data to create business impact.
The reliability of data may be compromised by a variety of factors, such as:
Credibility of Data Sources. 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 conformity to industry standards.
Human Errors Data entry and recording errors can cause inaccuracies in a dataset, reducing its reliability. Standardized procedures and training are essential to avoiding these mistakes.
Backup and storage: A backup plan, like 3-2-1 (3 copies on 2 local devices plus 1 offsite), reduces the risk of data loss due to hardware failures or natural disasters. Physical integrity is another aspect to consider, with companies that use multiple technology providers needing to ensure that the physical integrity of their data across all systems is preserved and protected.
Reliability is a thorny subject. The most important thing is that a business uses reliable and high-quality data to make informed decisions and generate value. To do this, businesses have to establish an environment of trust in data and ensure that their processes are designed to deliver trustworthy results, including adopting standard methods, educating data collectors and providing reliable tools.
