What is Data Quality Control?

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  • Written By: Malcolm Tatum
  • Edited By: Bronwyn Harris
  • Last Modified Date: 27 September 2019
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Data quality control is a strategy that involves controlling how data is used in the course of an application or some type of process. The idea is to make sure that the data is not corrupted during its use, and remains viable for use in future tasks. Control procedures are usually engaged once the data has gone through a quality assurance process that helps to ensure that the information currently on hand is accurate, complete, and consistent.

It is important to note that both data quality control and data quality assistance are important when it comes to maintaining useful information. The quality assurance process focuses mainly on verifying information as it is received, but before it is actually added to the main body of data that is used for various purposes. For example, a quality assurance function with the maintenance of a mailing list would involve qualifying each address in advance, to make sure that address is current, complete, and accurate. Should the client move at some time in the future, solid quality assurance would involve updating the address listing to reflect the most current status.


With data quality control, steps are taken to make sure data is not damaged or corrupted when it is actually used for some purpose. Using the example of the mailing list, quality control would take place when software is used to generate mailing labels that do not skew the information in any manner, such as transposing postal codes among the addresses pulled for use in the mailing project. The idea behind quality control is to protect information so it is not lost or altered during use, making it possible to utilize the data repeatedly for other purposes in the future.

When data quality control is not present, the corruption of the information can lead to serious consequences. In terms of a manufacturing operation, the feeding of corrupted data could lead to the production of products that are outside the scope of what customers order, making the finished goods unacceptable to fill standing orders. Corruption in customer data files can lead to double-billing customers or possibly applying payments to the wrong invoices, leading to undesirable interactions with those clients. When maintaining the data is key to tasks that involve the well-being of individuals, such as patients in a hospital or healthcare facility, data quality control helps to prevent the development of misinformation that could have a detrimental impact on the treatment process, possibly placing the life of the patient in danger.

Using a combination of data quality control and quality assurance helps to keep data current, identify and correct inconsistencies, and in general keep information usable for a variety of purposes. Part of the information technology systems task is to make sure storage programs used to maintain data banks are functioning properly and that procedures governing the entry and updating of data are observed at all times. Doing so helps to ensure that the information considered vital to the business operation is of the highest quality and capable of aiding in producing the desired results.


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