Reliability of data protection refers to the degree to the extent that a company’s data is accurate, trustworthy and reliable over time. Data provided by a company has to be reliable to be used in analysis and decision-making.
Companies must follow strict quality control procedures in order to ensure the accuracy of data. These include checks for data validation as well as standard formats and comprehensive data cleansing procedures. The experience and expertise of data collectors is also essential, as a seasoned team is more likely to adhere to the best practices and create reliable data. Secure data storage and a technological infrastructure that is up to date will also help avoid errors which could affect data reliability.
Incorrect or inconsistent data can result in serious issues both internally and externally. For instance in the event that a database for a business shows that a customer has $1000 on their account, when in reality they have only $100 due to an error in the data which could result in sanctions and even loss of trust. Inaccurate sensor data from manufacturing equipment could also cause recalls and product defects.
Validity and reliability are related but different concepts. Validity is determined by whether the information is correct. For example, a list with duplicate or non-unique email addresses is not valid and can’t be used to send out marketing emails.
Reliability concerns the consistency and accuracy of that data over time. For instance, if you’ve got two lists of customer email addresses from different sources that are identical but slightly different, you shouldn’t apply them to a specific marketing campaign because they will not be effective or will reach the wrong people. This is why it is vital to keep detailed records of the methods employed for obtaining and altering data to ensure the integrity and data protection transparency of the information.