Data protection reliability refers to the degree at the extent that a company’s data is reliable, accurate and consistent over time. A business’s data must be reliable to be useful for analysis and making decisions.
Businesses must adhere to strict quality control procedures to ensure the accuracy of data. These could include checks for data validation along with standard formats and rigorous data cleansing procedures. Experience and expertise of the data collection teams is crucial. A knowledgeable team is more apt to follow best practices and provide reliable data. Similarly, adequate technology infrastructure and secure storage capabilities can reduce errors that could impact data reliability.
Utilizing inaccurate or inconsistent data can cause serious problems both internally and externally. A data error could cause a company to show that a customer’s account has $100 when it actually holds $1000. This could result in financial penalties as well as an erosion of confidence. Inaccurate sensor data from manufacturing equipment could cause recalls and product defects.
Validity and reliability are related but are two different concepts. Validity is about ensuring that the information you’ve got is correct. For example an email list of customers email addresses that aren’t unique or that contain duplicate entries means that the list isn’t valid and cannot be relied on to send marketing emails.
Reliability is about the accuracy and consistency of that data over time. For example, if you have two lists of email addresses for customers from different sources that are identical but slightly different, you cannot apply them to a specific marketing campaign as they won’t be effective or may not reach the correct people. For this reason, it is crucial to keep detailed records of the methods used for collecting and modifying information, to ensure transparency and integrity of insights.