Data protection reliability is the process of ensuring that data is accurate complete, safe, and secure throughout its lifecycle from creation until archival or deletion. This involves protecting against unauthorized access, data corruption, and mistakes by taking robust security measures, routine audits, and checksum verifications. Data reliability is essential for enabling confident and informed decisions, giving organizations the ability to harness data to make a difference in business.
Data reliability can be harmed due to a variety of factors, not just
Credibility of the Data Source. A dataset’s trustworthiness and credibility are heavily dependent on its provenance. Credible sources are those with a a proven track record for producing reliable information. They can be verified through peer reviews, expert validations, or industry standards.
Human Errors Data entry and recording errors can cause inaccuracies in the data, which can reduce its reliability. Standardized procedures and training are crucial to avoid these errors.
Backup and Storage: A backup plan, such as the 3-2-1 method (3 copies on two local devices and one offsite) can reduce data loss caused by hardware malfunctions or natural disasters. Physical integrity is also a consideration, with organisations leveraging several technology vendors having to ensure that the physical integrity of their data across all systems can be maintained and protected.
Reliability is a thorny subject. The most important aspect is that a company uses reliable, high-quality data to make decisions and create value. To do this, businesses must create an environment of trust in data and ensure that their processes are designed to yield reliable results, which includes adopting standard methods, educating data collectors, and offering reliable tools.