Reliability of Data Protection
Data protection reliability is the process that ensures data is accurate, complete and secure during its entire lifecycle, from its creation to the time of archival or deletion. This includes securing against unauthorized access to data, corruption and errors by utilizing robust security measures, audits and checksum validations. Data reliability is critical to enable confident and informed decisions, giving organizations the ability to utilize data for business impact.
The reliability of data can be shaky due to a variety of reasons, including:
Data Source Credibility. A dataset’s reliability and credibility are heavily dependent on its provenance. Credible sources are those that have a a proven track record for providing reliable data. They can be verified by peer reviews, expert validations, or industry standards.
Human error – Data entry and recording errors can lead to inaccuracies in a dataset reducing its reliability. Standardized processes and training is essential in preventing these errors.
Backup and Storage: A backup strategy, like the 3-2-1 method (3 copies on two local devices and one offsite) reduces data loss from natural disasters or hardware malfunctions. Physical integrity is a further consideration, with organisations leveraging several technology vendors having to ensure that the physical integrity of their data across all systems can be maintained and secured.
Reliability of Data is a complex issue, with the most important aspect being that a company is using reliable and high-quality data to drive decisions and create value. To do this, businesses must create an environment of trust with data and ensure their processes are designed to produce reliable results. This includes implementing standardized methods, educating data collection staff, and offering reliable software.