Data protection reliability refers to processes that guarantee that personal data is collected legally, stored securely and never used or shared in violation of the rights of a person. It covers everything from ensuring data collection tools adheres to industry standards, to instructing data collectors and creating clear guidelines for data management.
It is essential to differentiate between data reliability and data validity, since they have different implications for business. Data reliability is concerned with the consistency of the data (such an issue of whether the same results would be achieved by repeating the measurement), while data validity is more concerned with accuracy (such as whether it accurately determines what it is supposed to measure).
Unreliable data could have many negative effects. For instance the case of a company that relies on unreliable information for making decisions or for deciding on its strategy, it could end spending resources in projects that are not profitable. It could also cause a loss of trust among employees, customers and partners, and reduce accountability. In some cases, using inaccurate data could have legal and regulatory implications.
There are numerous ways to improve the reliability of data. Implementing standard methods, training the data collectors and supplying reliable tools are among the most efficient methods. It’s also crucial to create clear data retention policies and establish feedback loops for data users to report errors. Additionally, it’s essential to maintain the integrity of data by making sure that all systems are properly backed up and that the recovery and backup processes function as intended.