Data protection is a matter of trust. It refers to processes that guarantee that personal data is collected legally, safely stored and never shared or used in violation of the rights of a person. It includes everything from ensuring that data collection tools conform to industry standards, teaching the data collectors and establishing clear guidelines for data management.
It is important to differentiate between data reliability and data validity, as they have different implications for business. While data reliability focuses on consistency (such as whether the same result would be obtained by repeating the measurement) Data validity is more concerned with the accuracy of the data (like whether it accurately measures what it meant to measure).
Unreliable data can result in negative consequences. If a company relies upon unreliable data for making decisions, it may result in wasting money or investing in non-profitable initiatives. It can also affect trust between employees, customers, and partners. In some instances, the use of inaccurate data could have legal and regulatory consequences.
Improving data reliability is a complicated task however, there are numerous methods to achieve this. Implementing standard procedures, educating the data collectors and supplying reliable tools are among the most efficient strategies. It’s also vital to establish clear policies for data retention and create feedback loops for users to report errors. It is also essential to ensure the integrity of data by ensuring that all systems are protected and recovery and backup processes work in the way they were intended to.
