2024/2025
MA-MMBFO2001U Analytics and Big Data
| English Title |
| Analytics and Big
Data |
|
|
| Language |
English |
| Course ECTS |
2 ECTS |
| Type |
Mandatory |
| Level |
Part Time Master |
| Duration |
One Quarter |
| Start time of the course |
Autumn |
| Timetable |
Course schedule will be posted at
calendar.cbs.dk |
| Study board |
Study Board for Full-Time MBA
|
| Course
coordinator |
- Dolores Romero Morales - Department of Economics
(ECON)
|
| Main academic
disciplines |
- Information technology
- Marketing
- Statistics and quantitative methods
|
| Teaching
methods |
|
|
|
Last updated on
04-06-2024
|
| Learning objectives |
- Understand the use of Regression Analysis in Decision Making,
such as in Business Forecasting
- Understand the use of Optimization in Decision Making, such as
in Portfolio Optimization
- Understand the use of Risk Analysis in Decision Making, such as
in Financial Investment
- Understand the use of Decision Analysis in Decision Making,
such as in Project Management
- Appreciate the implications of uncertainty in Decision Making
and the need for flexible and robust solutions
- Understand the potential Big Data has for different industries
and different departments in the organization
|
| Examination |
|
Analytics and
Big Data:
|
| Exam
ECTS |
2 |
| Examination form |
Home assignment - written product |
| Individual or group exam |
Individual exam |
| Size of written product |
Max. 10 pages |
| Assignment type |
Written assignment |
| Release of assignment |
An assigned subject is released in
class |
| Duration |
Written product to be submitted on specified date
and time. |
| Grading scale |
7-point grading scale |
| Examiner(s) |
One internal examiner |
| Exam period |
Winter |
| Make-up exam/re-exam |
Same examination form as the ordinary exam
|
Description of the exam
procedure
It is allowed to use GenAI on your exam, but you must declare
your use in an open and transparent way so assessors at all times
can distinguish between your own intellectual and autonomous
contributions and those that originate in interactions with a GenAI
platform. If you use GenAI for ideation or generation of content,
you must mention this in the methodology or introduction section of
your paper. Whenever you draw on GenAI output in the body text of
your paper, you need to declare this by leaving in both the
prompt and the relevant part of the response as well as a
citation. On top of this, you need to leave the full response as an
appendix for context.
|
|
| Course content, structure and pedagogical
approach |
|
In the current competitive environment, being able to extract
value from business data is both a crucial skill for individuals
and a main source of competitive advantage for firms. This includes
understanding the relationships between different business factors,
forecasting trends, appreciating the risks arising from management
actions, and optimizing investment strategies. Decisions are often
taken under considerable uncertainty and time pressure. Therefore,
managers need to be able to grasp the range of uncertainty rapidly
and make rational decisions, which are both flexible and robust.
This course aims to enhance your ability to apply modern Analytics
tools to decision-making. It is a practical course, which uses
computer software to illustrate how to apply the methodologies
introduced. Extensive use will be made of the popular spreadsheet
software, Excel. The course is multidisciplinary with
links to accounting, economics, finance, marketing and operations
management.
|
| Description of the teaching methods |
| The lectures will be based on texbook readings,
articles, cases and a high level of student
participation. |
| Feedback during the teaching period |
| During the teaching period, one-to-one feedback
will be provided during the workshops and the office
hours. |
| Student workload |
| Teaching |
24 hours |
| Preparation |
20 hours |
| Examination |
15 hours |
|
Last updated on
04-06-2024
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