A study on ways to make employment improve through Big Data analysis of university information public

The necessity of this study is as follows. A decrease in the number of newborns, an increase in the youth unemployment rate, and a decrease in the employment rate are having a fatal impact on universities. To help increase the employment rate of universities, we intend to utilize Big Data of university public information. Big data refers to the process of collecting and analyzing data, and includes all business processes of finding data, reprocessing information in an easy-to-understand manner, and selling information to people and institutions. Big data technology can be divided into technologies for storing, refining, analyzing, and predicting big data. The purpose of this study is to find the vision and special department of a university with a high employment rate by using big data technology. As a result of the study, big data was collected from 227 universities on www.academyinfo.go.kr site, We selected 130 meaningful universities and selected 25 universities with high employment rates and 25 universities with low employment rates. In conclusion, the university with a high employment rate can first be said to have a student-centered vision and university specialization. The reason is that, for universities with a high employment rate, the vision was to foster talents and specialize, whereas for universities with a low employment rate, regional bases took precedence. Second, universities with a high employment rate have a high interest in specialized departments. This is because, as a result of checking the presence or absence of a characterization plan, universities with a high employment rate were twice as high (21/7). Third, universities with high employment rates promote social needs and characterization. This is because the characteristic departments of universities with high employment rates are in the order of future technology and nursing and health, while universities with low employment rates promoted school-centered specialization in future technology and culture, tourism and art. In summary, universities with high employment rates showed high interest in student-centered vision and development of special departments for social needs.