Analaysis of university informatics technical services datas with data mining

The size and storage conditions of meaningful data have increased through the developments in information technologies and the convenience of these developments. In the past, data was stored in local databases within companies instead of today's large data collection centers and interpreted by managers. However, with the increase of bandwidth in internet access and the expansion of data storage systems, databases have become accessible and manageable from a single point for large enterprises and organizations even though they are now located in remote locations. The more the size and properties of data increased, the more it becomes very difficult to separate and interpret the data that expresses meaningful event from the existing data. Based on these improvements, a new branch of science called as data mining has been appeared. Today, data mining is widely used in data analysis and in extracting meaningful information from data. The obtained information at the end of the analysis process is used in decision support systems, future predictions and expert system entries. Because of the fact that present essential technologies occupy an important situation in human life, the continuity of information services has gained more importance. Within the scope of this MSc thesis, the numerical analysis of the services carried out through the information technology services of the universities has been performed and predictions for the next term have been made. To perform the aforementioned process, data between the years of 2013 and 2018 in Fault and Demand Notification System of Duzce University Information Technologies Department were used. The technical service and support systems existing in many public institutions and private companies are compatible with the decision support system offered by this thesis. Keywords: Data, Data mining, Technical service decision support systems.