Only quality data with integrity should be entered into systems, otherwise the data should not be used in calculations or trusted to make decisions.
The following is a table showing all the characteristics of data integrity.
| Characteristic | Description | Example of compromise |
|---|---|---|
| Accuracy | How close a data is to the real-world value. | A customer enters their age as 210. |
| Authenticity | Data comes from a genuine, verified and authentic source. | A discount code is reused by someone who didn’t earn it. |
| Correctness | Data follows the rules and constraints of the system (follows intended structure, within allowed ranges, meets validation criteria, follows legal/business goals and objectives). | A one-time-use code is reused. |
| Reasonableness | Data is appropriate contextually (is it believable?) | A customer enters their age as 210. |
| Relevance | Data is appropriate for the function/purpose. | Customer’s shoe size in a dataset used for a rewards program. |
| Timeliness | Data is up-to-date and available when needed | Outdated user addresses for deliveries |