2018/2019
BA-BINMO2012U Business and Data Analytics
| English Title |
| Business and Data
Analytics |
|
|
| Language |
English |
| Course ECTS |
7.5 ECTS |
| Type |
Mandatory |
| Level |
Bachelor |
| Duration |
One Quarter |
| Start time of the course |
Spring |
| Timetable |
Course schedule will be posted at
calendar.cbs.dk |
| Study board |
Study Board for BA in Information
Management
|
| Course
coordinator |
- Matthias Trier - Department of Digitalisation
- Signe Dyrby - Department of Digitalisation
|
| Main academic
disciplines |
|
|
| Teaching
methods |
|
|
|
Last updated on
02-05-2018
|
| Learning objectives |
- Describe, compare and select techniques and tools for business
and data analytics
- analyze example datasets of quantitative business data
- visualize example data to support business decision making
- critically reflect on issues of quantifying business
decisions
- apply techniques and tools to practical cases
- assess and criticize the scope of techniques and tools as well
as their relevance for practice
|
| Examination |
|
Business and
Data Analytics:
|
| Exam
ECTS |
7,5 |
| Examination form |
Home assignment - written product |
| Individual or group exam |
Individual exam |
| Size of written product |
Max. 10 pages |
| Assignment type |
Written assignment |
| Duration |
Written product to be submitted on specified date
and time. |
| Grading scale |
7-step scale |
| Examiner(s) |
One internal examiner |
| Exam period |
Spring |
| Make-up exam/re-exam |
Same examination form as the ordinary exam
|
Description of the exam
procedure
Participants of the course will report on their analysis of a
case dataset with the objective to elicit valuable insights from
raw data that can prepare data-driven decisions at a management
level. The approach and the results are documented as a project
report and are submitted before or at the specified
deadline.
|
|
| Course content and structure |
|
Taking the perspective of an information manager, this course
aims to provide students with the ability to use techniques and
tools of data analytics that are relevant for the modern
data-driven organization and its management. This involves
approaches to manipulate and analyse quantitative business data,
relating to fields such as employee analytics, operation analytics,
or consumer analytics, using example datasets and software tools.
Related to the analysis, the course also addresses relevant formats
and structures of data repositories, such as tables, files and
databases, as well as common meta-data and data exchange standards.
We address options and challenges with the visualization of data
and the related question of how to communicate results. Further
topics include: issues of making decisions based on a reduced,
quantified view on the business context and reflect on the future
challenges of a (big-) data driven business.
|
| Description of the teaching methods |
| Based on the principles of student-centred
learning, the learning methods will be a mix of interactive
lectures, practical computer-based analysis work, as well as group
and class discussions. |
| Feedback during the teaching period |
| The students will receive feedback on their
project work in workshops during the course. They can further
inquire with the teacher to get feedback about their exam
results. |
| Student workload |
| Lectures |
24 hours |
| Workshops |
6 hours |
| Preparation for Classes |
90 hours |
| Project Work |
70 hours |
| Exam |
16 hours |
| Total |
206 hours |
|
Last updated on
02-05-2018
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