• Data integrity refers to the accuracy and completeness of data entered in a computer or received from the information system. Integrity is measured in terms of accuracy, timeliness and relevance of data.

• Accuracy
• It refers to how close an approximation is to an actual value. As long as the correct instructions and data are entered, computers produce accurate results efficiently. In numbers, the accuracy of a real number depends on the number. For example, 72.1264 is more accurate than 72.13.

• Timeliness
• This is the relative accuracy of data in respect to the current state of affairs for which it is needed.
• This is important because data and information have a time value attached to them. If received late, the information may have become useless to the user. For example, information in the newspaper that is meant to invite people for a meeting or occasion must be printed prior to the event and not later.

• Relevance
• Data entered into the computer must be relevant so as to get the expected output. In this case, relevance means that the data entered must be pertinent to the processing needs at hand and must meet the requirements of the processing cycle. The user also needs relevant information for daily operations or decision making.

Threat to data integrity

• Threats to data integrity can be minimized through the following ways:
• Backup data preferably on external storage media.
• Control access to data by enforcing security measures.
• Design user interfaces that minimize chances of invalid data entry.
• Using error detection and correction software when transmitting data
• Using devices that directly capture data from the source such as bar code readers, digital cameras, and optical scanners.