2021/2022 DIP-DHDVV7005U Business Intelligence & Data Analytics
English Title | |
Business Intelligence & Data Analytics |
Course information |
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Language | English |
Course ECTS | 5 ECTS |
Type | Elective |
Level | Graduate Diploma |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 50 |
Study board |
Study Board for Graduate Diploma in Business Administration
(part 2)
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Course coordinator | |
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Study administration for GD SCM: HDSCM@cbs.dk | |
Main academic disciplines | |
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Teaching methods | |
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Last updated on 26-03-2021 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||
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Examination | ||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||
Business Intelligence & Data Analytics delves into decision-making, thereby covering business analytics, as well as predictive and learning approaches. The students will receive knowledge about phenomena related to business intelligence & data intelligence, and the necessary skills that help them to appraise methods to deal with these phenomena in an effective way. Lectures aims at framing the business and operations problem areas and then, concentrate on the discussion of practical dilemmas faced by managers. Teaching is practically oriented. The discussion of managerial issues allows students to acquire a better understanding of the type of data needed to reach a solution for the problem under consideration. Furthermore, the implications of the quality of data and how it impacts the solution of the problem at stake are thoroughly explored. Examples of management areas covered in the course include demand forecasting, inventory management, and supply chain coordination.
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Description of the teaching methods | ||||||||||||||||||||||||
The course is structured in 3 interconnected
modules, namely (i) Business Analytics, (ii) Artificial
Intelligence, Machine Learning & Predictive Approaches, and
(iii) Business Intelligence and Data Analytics. The modules are
structured in a way to ensure course progression. The curriculum
covered on each lectured will be used as a background for the
subsequent ones. The modules cannot be seen as stand-alone pieces.
Lectures aims at framing the business and operations problem areas and then, concentrate on practical dilemmas faced by managers. The discussion of managerial issues allows students to acquire a better understanding on the type of data needed to reach a solution for the problem under consideration. Furthermore, the implications of the quality of data and how it impacts the solution of the problem at stake are thoroughly explored in classroom. Thus, management problems work as a mean to convey the theory, and to explore its implications and limits. The teaching method assures students involvement and participation. This is achieved by the use of managerial issues and problems, and assignments to be presented in class. |
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Feedback during the teaching period | ||||||||||||||||||||||||
Feedback will be offered during the course in three distinct ways. First, students will get feedback during the lectures in the form of interaction with the teacher if any question arises. During some sessions, there will be short workshops to discuss some management issues. At these workshops, students will receive one on one feedback on their individual inquiry (on demand). That is to say, during the workshops, students can request instructors to clarify their specific questions on the assignment and on the curriculum, in order to provide recommendations to the managerial dilemma that are to be addressed on that session. Third, also during the workshops, the instructor will provide summative feedback to the class by addressing the challenges perceived during the one on one interaction. It is expected that students actively participate in lectures and workshops. Additional individual feedback can be obtained during the office hours. | ||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||
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Further Information | ||||||||||||||||||||||||
The course consists of a total of 26 lessons (5 ECTS).
Tuesday in week: 41,44,45, 46 Thursday in week:40, 41,44,45,46
There is no teaching in week 42
For further information, please contact the Department of
Operations Management
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Expected literature | ||||||||||||||||||||||||
The expected literature will be announced during the course. |