The security of data is the degree to which data collected by a business are accurate, reliable and consistent. Data from a business’s must be reliable for it to be useful for analysis and making decisions.
To ensure data integrity, businesses should adopt and adhere to strict quality control procedures. This could include things like validation of data, standard formats, and rigorous data cleaning procedures. Experience and expertise of the data collection teams is also important. A team with experience is more likely to follow best practices and provide reliable data. A secure storage option for data and a technological infrastructure that is current can help to prevent errors that could affect the reliability of data.
The use of inaccurate or inconsistent data can lead to serious problems, both internally and externally. A data issue can cause a company to show that a customer’s account has $100 when in reality it’s $1000. This can lead to financial penalties and the loss of confidence. Inaccurate sensor data from manufacturing equipment could also lead to recalls and product defects.
Validity and trust are connected but different concepts. Validity is determined by whether the data is accurate. For example the list that has duplicate or non-unique email addresses is not valid, and therefore cannot be used to send marketing emails.
Reliability refers to the accuracy and consistency of the data over time. For instance, if you have two lists of email addresses for customers from different sources that are similar but slightly different, you can’t apply them to an individual marketing campaign since they will not work or will reach the wrong people. To ensure transparency and integrity it is essential to keep detailed records on the methods used to collect and edit data.