2023/2024 DIP-DHDVV7008U Business Analytics: Data-Driven Decision Making
English Title | |
Business Analytics: Data-Driven Decision Making |
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 HD SCM: HDSCM@cbs.dk | |
Main academic disciplines | |
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Teaching methods | |
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Last updated on 29-03-2023 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||
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Examination | ||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||
Business Analytics delves into decision-making, thereby discussing business analytics, as well as predictive and learning approaches. The students will receive knowledge about phenomena related to business analytics - data driven decision making, and the necessary skills that help them to appraise business approaches to deal with these phenomena in an effective way. The course is structured in 3 interconnected modules, namely (i) Data Driven Operations, (ii) Artificial Intelligence, Machine Learning & Predictive Approaches, and (iii) Business Analytics - Data Driven Decision Making. 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 the discussion of practical dilemmas faced by managers. 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 teaching method is centered on a dialogue
that will allow students to grasp the business and operations
problem under consideration and, at the same time, discuss
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 and argue
for the selection of a suitable approach to tackle it. 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). For information relating to the course please go
to: https://cbscanvas.instructure.com/ Monday week 40,43,44,46 from 18.05 - 20.40 Wednesday week 40 from 18.05 - 20.40 Wednesday week 41 from 17.10 - 19.45 Saturday in week 44, 46 from 08.55 - 12.25
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. |