Reliability of data protection is the process of ensuring that data is accurate complete, safe, and secure throughout its entire lifecycle from creation to archival or deletion. This includes protecting against unauthorized access to data, corruption, and errors with robust security measures, audits and checksum validations. Reliability of data is essential to enable confident and informed decisions, allowing businesses to make use of data to create business impact.

Data reliability can be harmed due to a variety of factors, not just

Credibility of the Data Source. The trustworthiness of a dataset and its credibility are heavily dependent on its provenance. Credible sources are those that have a proven track record for providing reliable data. They can be verified by peer reviews, expert validations or industry standards.

Human errors – Data entry and recording mistakes can introduce inaccuracies to an information set, which can reduce its reliability. Standardized processes and training are crucial to avoiding these mistakes.

Backup and storage: A backup strategy, such as the 3-2-1 method (3 copies on two local devices plus one offsite) helps to prevent data loss due to natural disasters or hardware malfunctions. Physical integrity is also a issue, with organizations that rely on multiple technology vendors needing to ensure that the physical integrity of their data across all M&A transactions systems is preserved and protected.

Reliability is a complex topic. The most important thing is that a business uses reliable and high-quality data to make informed decisions and generate value. To achieve this, companies must establish an environment of trust in data and ensure that their processes are designed to yield reliable results. This includes adopting standardized methods, training data collection staff, and offering reliable software.