It is an ever-present point of discussion in many companies, regardless of department or duties. Data quality can be evaluated based on a number of parameters.
The purpose of this series in five parts is to increase the understanding of these, but also to give a picture of how these can be improved.
The first dimension we focus on is data accuracy, or correctness in Swedish. Accuracy is a measure of how correct the information is. Inaccuracies in the information can come from incorrect input data or simply missing data. Below are examples of activities to raise data accuracy to a level that is acceptable:
Develop clear job descriptions for personnel who work with data in the business. Training the staff in the handling of the systems that are used on a daily basis is an effective way to improve data accuracy.
Carry out automatic checks of important data points, for example: as amount range, format, list of allowed values and more. Checks can also be done manually but this is very time consuming and introduces new sources of error and person dependency. Time that can be spent on developing the business instead.
Does your business have routines for this today? Or do you have other ways to ensure that your data is correct?
Are you curious to learn how Business Cloud iPaaS can help your company with integrations and data quality? Contact me below or book a demo and I'll tell you more.
Staffan Hedbrandh, CEO