Knowledge discovery in library database using data mining techniques

A continuous increase in the amount of recorded data has introduced a new thing "Big Data" nowadays, which is named as "the IT Era" when information systems are quite developed. Obtaining highly important strategic informations for especially managerial decision makers is only possible when big data is processed correctly. Data mining techniques are often used to reach meaningful and useful information from the data stacks. The purpose of this study is that, information systems managers of university libraries providing data-oriented services can create user profiles and accordingly, they will be able to effectively make future investment decisions. In this study, an application has been made of the information system of Erzincan Binali Yıldırım University central library. Through clustering and association rule analyses which are among descriptive models, data such as library inventory member profile, publication borrowing habits and borrowed publications were obtained and an evaluation was made according to these data at the end of the study.