Characteristics of Quality Data
People depend on the systems they use to contain high‐quality data. If
they find the data to be wrong, outdated, or incomplete, they begin to
distrust the system and will likely stop using it. If the data in the system is
personally important to the individual, such as the data in payroll or
medical systems, then there is a strong need to have it corrected as
quickly as possible.
What are the characteristics of good‐quality data? There are a variety of
characteristics, but we will focus on six. Let's look at the data that may be
in a payroll system and how each of the characteristics of quality data are
important, and consider an example of each.
• Accuracy – Is the information correct? For example, is the annual
salary correct?
• Completeness – Is all the information there? For example, if overtime
was worked, is it included?
• Timeliness – Is the information current and pertaining to a specific,
identified time period? Does the payroll data pertain to the current
pay period? For example, is old, outdated data used, which could
change the amount paid to the employee?
• Uniqueness – Does each record have its own individual identifier
(often referred to as a unique identifier)? Does the payroll record
apply to a specific individual? For example, does a specific payroll
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record pertain to a specific employee?
• Validity – Is the information appropriate for defined parameters? Is
the data in the payroll record based on the acceptable ranges? For
example, is the hourly rate within the accepted range and is the
number of hours worked reasonable?
• Consistency – Does the data correctly align with other data in the
system? For example, if the employee is a salaried employee does the
payroll record reflect that vs. hourly employee data?
It is important that the data in information systems is of high quality. As
systems are developed, the testing should include ensuring that the
quality of data is maintained throughout the system, from its source to
the final output. Therefore, data needs to have these characteristics when
it is entered into the system. The data entry process should include
validation that it meets these quality attributes, and then it needs to be
protected as it resides in and flows through the system. If any of these
characteristics are missing, the system must be analyzed to discover
where the problem lies. The correction may be as simple as fixing an
individual record; or, if it is not clear where the problem lies, the system
may be considered unreliable overall and may need to be taken offline
until corrections are applied. When migrating data to a new system, it is
also important to maintain accuracy and integrity. Inconsistency or
redundancy in data will reduce the acceptance of a new system by users.
Part of a system implementation plan should include specifics about how
data will be transferred, entered, and verified to ensure a high degree of
accuracy (often referenced as a data migration plan).
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