Data protection reliability is the process of ensuring that data is accurate complete, secure, and safe throughout its lifecycle from creation until archival or deletion. This includes safeguarding against unauthorized data access, corruption, and errors with robust security measures, audits and checksum validations. Data reliability is vital to make informed and confident decisions, empowering organizations with the ability to harness data to enhance business performance.
The reliability of data can be impacted by a variety of factors, including:
Data Source Credibility: A dataset’s credibility and reliability are greatly dependent on its provenance. Credible sources are those that have an established track record of producing reliable information. They can be verified by peer reviews, expert validations or industry standards.
Human errors Data entry and recording mistakes can result in inaccurate data for a dataset reducing its reliability. Standardized processes and training is essential to avoiding these mistakes.
Backup and storage Backup and Storage like 3-2-1 (3 copies on two local devices and 1 offsite) reduces the chance of data loss due to natural disasters or hardware failures. Physical integrity is another aspect to consider, with companies that use 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 matter, with the most important factor being that a company uses reliable and reliable data to inform decisions and generate value. To achieve this, organizations need to engender confidence in data and ensure that their processes are designed to produce trustworthy results, including adopting standard methods, educating data collectors, and supplying reliable tools.
