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Class Business Intelligence Applications

  • Presentation

    Presentation

    The discipline of Business Intelligence Applications has as its fundamental objective providing the student with knowledge and competence in the areas of decision support through techniques and methodologies that allow the effective exploration of data and its transformation into knowledge.

     

    It is also intended to provide students with the possibility of developing skills in the use of tools to provision, explore, analysis and communication of information.

     

    The practical component is a key attribute of the discipline. The ability to identify and build indicators that can support analytical decisions is highly valued.

  • Code

    Code

    ULHT457-1-13321
  • Syllabus

    Syllabus

    1. Trends in Data, Analytics and Business Intelligence
    2. Business Intelligence application areas: context, objectives and relationship with business processes
    3. Data Modeling and project methodologies in Business Intelligence
    4. Data Visualization Techniques
    5. Extracting Knowledge from Data
  • Objectives

    Objectives

    When concluding this curricular unit, the student should:

    • Understand the Business Intelligence (BI) market, its relationship with related areas (analytics, data mining) and describe how organizations survive and stand out in a strongly competitive environment, solving problems and taking advantage of opportunities;
    • Understand the need for computerized and operationalized support in the decision-making process;
    • Describe the methodology and concepts of BI focused on the extraction of the information and the discovery of knowledge in the data;
    • Understand the main issues in the implementation of BI systems and describe methodological approaches that facilitate their success.
  • Teaching methodologies and assessment

    Teaching methodologies and assessment

    The subject has a strong practical component where students have to apply their knowledge to modern cloud technology and obtain visible results.

  • References

    References

    • Santos, M., & Ramos, I. (2017). Business Intelligence Da Informação ao Conhecimento (3ª Edição Atualizada). FCA – Editora de Informática, Lda.
    • Chapman, P., Clinton, J., Kerber, R., Khabaza, T., Reinartz, T., Shearer, C., & Wirth, R. (2000). Crisp_DM, Step-by-step data mining guide. SPSS Inc., 9(13), 1-73.

     

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