Data protection reliability is the process used to ensure that the accuracy, completeness and secure throughout its lifecycle, from its creation to the point of archival or deletion. This includes protecting against unauthorized access to data, corruption, and errors with robust security measures, audits, and checksum validations. Data reliability is vital to ensure that you can make informed and secure decisions, giving organizations the ability to use data to make a difference in business.

The accuracy of data can be compromised by a range of causes, including:

Data Source Credibility: A dataset’s credibility and trustworthiness are heavily impacted by its provenance. Credible sources have a track record of producing reliable data and are validated through peer reviews, expert validations, or adherence to industry standards.

Human Errors – Incorrect data entry and recording can result in inaccurate data for the accuracy of a data set, thus reducing its reliability. Standardized processes and proper training are necessary to avoid these errors.

Backup and storage A backup strategy, like 3-2-1 (3 copies on 2 local devices plus 1 offsite), reduces the risk of data loss due to physical failures or natural catastrophes. Physical integrity is another aspect to consider. Companies that utilize multiple technology vendors must ensure that the physical integrity of their data systems are safeguarded and maintained.

Reliability of data is a thorny issue with the most important aspect being that a company is using trusted and high-quality data to drive decisions and create value. To achieve this, companies must create the culture of trust in data and ensure that their processes are designed to produce reliable results. This means adopting standards-based methodologies, teaching data collectors and providing reliable tools.

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