Data integrity represents the accuracy, consistency, and trustworthiness of a set of data. It is vital to maintain data integrity to ensure that the data has not been changed or corrupted throughout its use. Maintaining data integrity involves maintaining strict procedures and implementing processes that prevent unauthorized changes and access to the data. There also must be measures in place to detect errors and ensure that the data remains accurate over time.
A set of data with strong data integrity will exhibit all of the following traits:
- Accuracy: error free, precise data
- Consistency: uniform, compatible across different systems
- Reliability: trustworthy, with no defects or corruptions
- Completeness: no missing records or elements
- Validity: fit predefined rules and constraints
- Timeliness: should be up to date
Without data integrity, a company cannot make data-based decisions as comfortably, as there may be errors in their data. Implementing measures to protect the integrity of an organization’s data should be seen as a priority. Strong data integrity means that a company can have more trust in their data, reduce the risk of breaches, use the data more efficiently, and improve data-based decision making.