Abstract
Effectively improving and enhancing the data quality of colleges and universities is the most fundamental goal of university data governance. In this paper, first of all, the causes of data quality problems in colleges and universities are analyzed, and then the general idea of improving data quality is put forward, in which introduces how to identify data quality problems, how to solve data quality problems through technical and business means and how to make the data quality management of colleges and universities form a long-term mechanism through the construction of the system.
Highlights
CAUSES OF DATA QUALITY PROBLEMSThe construction of digital campus in colleges and universities has shown an obvious characteristic, that is, it attaches importance to process, but ignores data and lacks standards
All of the above involves issues at the level of the overall data architecture that need to be thought about and solved primarily at the information center, which is the main driver for many schools to initiate data governance at the moment
(II) In the beginning, various data quality problems were caused by the inadequate design or low quality of the functional modules of various business system software
Summary
The construction of digital campus in colleges and universities has shown an obvious characteristic, that is, it attaches importance to process, but ignores data and lacks standards. Many staffs of business departments are lack of information literacy, and the information center has spent a lot of energy and funds to help these departments to build the information system, but the result is still delayed, or after the built system is handed over to the department, the department complains by various phone calls every day that the system is not easy to use or can't be used and other problems, and they are not willing to adopt it Another situation is that the department will often use the system for a period of time on the side, they ignore it, and return to the original off-line manual work state. If the quality of data is to be addressed, the cause of the quality problem must first be traced back to the source, just as with a doctor's visit, the prescription can only be effective if the diagnosis is correct
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