The output has seven parts: innovation, teamwork, conflict management, leadership, adaptability and flexibility, objective-based management, and planning. The process element has four parts: data preparation, modeling, evaluation, and development. The input element has three parts: student’s data, student activity, and observed behavior. The results of this research showed that (1) the student relationship management using business intelligence model consist of three elements: input, process, and output by using CRISP-DM in process element. The appropriateness questionnaire for the student relationship management using business intelligence model was created and submitted to five experts for improvement. In the second part, the researchers evaluated the appropriateness of the model. Then synthesized and designed the model for managing student relationships using business intelligence system based on various data analysis principles with CRISP-DM. There are two part for this research, at first part, the researchers studied about theories and research which relate to student relationship management, business intelligence, student affairs, and leadership. The purpose of this research is to develop Student Relationship Management Using Business Intelligence Model to Enhance Student’s Leadership in 21st Century and to evaluate the appropriateness of the model. The final part of the article presents a proposal for further work on IT systems for RTE in the context of existing trends such as DARQ technology (Distributed Ledger, Artificial Intelligence, Extended Reality, Quantum computing). Particular attention was paid to the analysis of success factors (determinants) in system design and the use of MUST methodology (MUST is a Danish acronym for theories of and methods for design activities). The article presents both literature analysis and the characteristics of own work on designing IT systems for RTE. The use of integrated systems such as ERP, CRM, SCM, and so on provides the ability to implement the main business processes of a real-time enterprise. Such a system is designed to provide employees and business partners with the information they need in real time. The article justifies the thesis about the need to build a system for the RTE’s requirements and the conditions of its implementation. It is a summary of our work on this type of system. The aim of the article is to present the basic problems of building an IT system that is the basis of a real-time information processing (RTE) company. Integrated IT systems supporting management constitute a common platform – the foundation of a real-time enterprise.
RTE provides real-time information to employees and business partners. Market requirements for immediate response to business changes became the basis of the idea of a real-time information processing (RTE) company. This poses many challenges for information technology. The current, fast market changes require enterprises to dynamically adapt the way they conduct their business. Organizations need to address potential challenges as part of a pre-project of a real time business intelligence implementation. The aim of this research is to contribute by visualizing how a real time business intelligence solution can shorten a complex decision process by giving the correct information to the right people. Visualization of the current decision processes showed that by adding a real time business intelligence solution it would help eliminate the use of intuition, as there would be more data available and the decisions can be made where the work is performed. By implementing an RTBI solution, it would provide the decision-maker with fresh and reliant data to base the decisions on. The objective of this research is to show that a real time business intelligence solution would be beneficial for supporting the operational and tactical layers of decision-making within an organization. Real time business intelligence (RTBI) presents numbers in real time, providing the decision makers at the operational and tactical layers with data as fresh as it can be.īy having accurate, fresher and a bigger amount of data, businesses will be able to make decisions in a faster pace, and eliminate tedious complexity of the decision-making process. Business intelligence (BI) helps businesses to make decisions based on good pre-analysis and documented data, and enables information to be presented when and where the decisions need to be made. Today's businesses need support when making decisions.
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