The security of data is the degree to which data that a company collects are reliable, accurate and constant. A business’s data must be reliable to be useful in analysis and making decisions.
To ensure data integrity businesses must establish and follow strict quality control procedures. This could include things like validation of data, standardized formats, and rigorous data cleaning procedures. Experience and expertise of the teams responsible for data collection are equally important. A knowledgeable team is more likely to follow best practices and provide reliable data. A good infrastructure and secure storage capabilities can help prevent errors that could compromise the accuracy of data.
Incorrect or inconsistent data could lead to serious problems both internally and externally. A data error can cause a company’s data to show that a customer’s accounts have $100 when in reality it’s $1000. This can lead to financial penalties and the loss of trust. Additionally, inaccurate sensor information from manufacturing equipment could result in recalls and product defects.
Validity and trust are connected but different concepts. Validity is based on the accuracy of the data. For example a list of duplicate or non-unique email addresses is not valid and can’t be used to send marketing emails.
Reliability refers to the consistency and accuracy over time of the data. For instance if two lists of customer email addresses from different sources are identical however, they are slightly different. they can’t be used to target an over here advertising campaign because they are not able to work or be able to reach the correct people. Therefore, it is important to keep complete records of the methods employed to collect and modify data, in order to ensure transparency and integrity of insights.