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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 communicate 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.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Master Degree | Semestral | 7
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULHT457-13321
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
Part 0: Data, Analytics, Data Science and Business Intelligence: Trends Part 1: Business Intelligence Application Areas, Context, Objectives and Relationship with Business Processes. Methodologies. Part 2: Modeling in Business Intelligence Part 3: Data provisioning and Preparation Part 4: Exploration, Description, and Visualization of Data
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Objectives
Objectives
When concluding this curricular unit the student should: Understand the Business Intelligence (BI) market, its relationship with related areas (analytics, data mining, data science) 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 and relate them to Decision Support Systems (DSS); Understand the main issues in the implementation of BI systems, nodded to the methodological approaches that facilitate their success.
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Teaching methodologies and assessment
Teaching methodologies and assessment
The subject has a strong practical component where students have to apply knowledge and obtain visible results.
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References
References
Grossmann, W., & Rinderle-ma, S. (2015). Fundamentals of Business Intelligence. Berlin Heidelberg: Springer-Verlag 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. Retrieved from https://www.kde.cs.uni-kassel.de/lehre/ws2012-13/kdd/files/CRISPWP-0800.pdf
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Office Hours
Office Hours
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Mobility
Mobility
No
