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Information Systems – Data Mining & Business Intelligence

The course aims to go deeper into topics related to Integrated Information Systems (IIS). In addition to the primary goal of understanding what an IIS is, what its requirements are, and what they are useful for in a modern organization, students have the opportunity to investigate more specialized issues. Some of the topics discussed are the technological infrastructures required, the changes needed in the operational and organizational structure of the organization, the operational intelligence, the data management and knowledge mining capabilities provided, the ethical and social issues that arise, etc.
  • Lecturer 1 : Giannis Tzimas
  • Semester : Semester 8
  • Lecturer 2 : Vasilis Tampakas

Moreover, the course aims at making students understand more practical aspects of both the data mining and the business intelligence processes in an information system. To this end, the students will apply their Machine Learning techniques knowledge acquired during the respective course to solve real-life problems using specific datasets.

Course content encompasses:

    • Integrated Information Systems Analysis and Design: what are the building blocks and their different levels of architecture? What is the life cycle of an IIS, and what is its purpose and utility in an organization?
    • Integrated Information Systems Analysis and Design: User requirements, system requirements, and design of different levels of IIS architecture.
    • IIS Categories and their applications. Executive Support Systems, Decision Support Systems, Management Information Systems, and Transaction Processing Systems.
    • Enterprise Resource Planning System (ERP): What are ERPs and their utility, an ERP system architecture, modern ERP systems, and their selection criteria.
    • Customer Relationship Management Systems (CRMs): What are CRMs and their utility, CRM system architecture, modern CRM systems, and their selection criteria.
    • Case studies of ERPs and CRMs: Customizing and managing ERP and CRM systems.
    • Data Mining
    • Business Intelligence.
    • Cloud computing technologies.
    • Security
    • Ethical and Social Issues arising from ICT Integration in an organization.