The quality of data is about shielding data from unauthorised maintenance, deletion, or alteration. This incorporates data validity.
Integrity, including its reliability and trustworthiness, has to do with the precision of details. Information with low integrity issues may be deemed unimportant or not appropriate for specific operational functions to search for errors vigorously. In order to avoid adverse effects on company operations, information with high integrity issues is deemed essential and must be correct.
Examples of data with high questions regarding honesty include:
- software code, which must be precise and unaltered to ensure proper operation of the application.
- system logs, which must be reliable and unaltered to ensure that intrusions and system modifications are properly detected.
When handling data integrity, remember the following:
- Whether data must remain precise and uncorrupted
- If data can only be altered by certain individuals or under certain conditions
- Whether data must come only from unique, trusted sources
Guidelines for data integrity
Follow these guidelines when managing data integrity:
- Data backup.
In the case that data is lost or corrupted, backup copies of data are critical. If the data cannot be recovered from a backup, even partially, then you can need to begin from scratch. - Enable logging.
For detecting changes to data, logs can be used. A log may help determine what data could have been changed and who is responsible for the change in incidents where data has been added, updated, or removed inappropriately or without authorisation. - Verify and validate data.
Through ensuring the data is accurate and acceptable at the time of use, you will reduce the likelihood that inaccuracies or incomplete data will impact company operations or other data dependent applications.