ISLA Santarém 12670

Information Systems for Management

• ApresentaçãoPresentation

  The course covers the study and management of information systems, exploring architectures, frameworks, and technologies that support digital transformation and artificial intelligence, promoting skills in the design, planning, and management of business solutions geared toward organizational objectives. 
• ProgramaProgramme

  1. Information systems concepts 2. Information systems management 3. Architectures and frameworks for information systems 4. Information systems design and modeling 5. Support systems and technologies applied to organizational management (ERP, GIS, CRM, SCM) 6. Artificial intelligence applied to management processes 7. Digital transformation in organizations
• ObjectivosObjectives

  Objectives: O1. Present the concept of system and its usefulness in the study of complex situations; O2. Present the concept of IS, O3. Describe and identify what an IS is; O4. Distinguish and compare different information systems; O5. Identify the basic functions of IS management; O6. Recognize the need to use frameworks and reference models in organizations; O7. Frame IS in the organization, through key reference concepts in IS management; O8. Present techniques and methods for the development and maintenance of information systems. O9. Discuss and deepen knowledge about information systems architectures. Competency Skills: C1. Know, analyze and design an architecture for business IS; C2. Plan and manage information systems projects suited to the organization's objectives. C3. Participate in the selection of information systems best suited to the organization's objectives.
• BibliografiaBibliography

  Laudon, K. &, Laundon J. (2021). Management Information Systems – Managing the Digital Firm, Global Edition. Marr, B. (2021). Data Strategy: How to Profit from a World of Big Data, Analytics and Artificial Intelligence, Kogan Page Ribeiro, R & Veiga, P. (2022). Transformação Digital - Os Desafios, o Pensar e o Fazer. Actual Editora. Jason L. Anderson, Jeffrey L. Coveyduc (2020). Artificial Intelligence for Business: A Roadmap for Getting Started with AI. Willey.
• MetodologiaMethodology

  In-person:  1. Expository method: presentation of each of the content topics. 2. Practical application through guided exercises to consolidate knowledge. 3. Laboratory practice: based on the Problem-Based Learning (PBL) methodology, aiming to find solutions to problems identified by students or proposed by the teacher. Independent: 4. Guided research proposed by the teacher to analyze practical cases proposed by the teacher. The teacher provides feedback on the development of the problem addressed in the laboratory practice (Tutorial Guidance - TG) in person in the classroom and/or through the Moodle teaching/learning support platform.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  5
• NaturezaNature

  Mandatory
• EstágioInternship

  Não
• AvaliaçãoEvaluation

  A avaliação curricular será concretizada através 2 momentos de avaliação: Projeto com componentes teórica e prática, valendo 50% da nota final (1 momento de avaliação) e outro teste 50% (2º momento de Avaliação). A avaliação final compreende a realização de um exame escrito (100%).