Although storing perfect data is effectively impossible, businesses should always strive to make data quality improvements.
SmartData Collective blogger Jim Harris has explained that making small improvements to information checking systems can help the way in which an organization is run and managed.
Indeed, the expert stated that any data quality projects undertaken should be built around a company's best practices.
Meanwhile, in an earlier post on his OCDQ blog, Mr Harris suggested that practitioners should work to the belief that there is "no such thing as data accuracy - there are only assumptions of data accuracy".
Accuracy, he explains, can be defined as both the correctness of a data value within a limited context combined with the correctness of a valid data value within an extensive context.
"Although accuracy is only one of many dimensions of data quality, whenever we refer to data as accurate, we are referring to the ability of the data to meet specific requirements and quite often it's the ability to support making a critical business decision," he confirmed.