M.Sc. Special Topics: Business Intelligence (BI)

Modul number: 04WI1101

The course is a 6 ECTS module and both the lecture and the exercise must be completed together in the same semester. Due to the interactive format of this course, the number of participants is limited. You can apply for the course using the special application form. Please note: You can only participate in this course after you have been admitted.

Please note: The course is full. We are not accepting any more applications.

Please read all following sections if you wish to attend the course.

Lecture

Time/Room

Start of the lecture: 31.10.2023

Room: The room number will be provided in the e-mail confirming your successful admission to the course

Note: The course is taught in a compressed format. There is no clear separation of lecture classes and exercises. The course will take place in the same room over the full period of four hours.

Participants

The course is primarily aimed at students in the Master's program. In justified cases, students in the Bachelor's degree program can also be invited to take part in this course. Participation in this course is only possible on application and only after admission. You can apply for the course using the special application form.

For Master's students, the course can alternatively be credited for the following module: 04WI2017 - Special Topics in Information Systems

Requirements (recommendation)

Prior attendance of Betriebliche Anwendungssysteme (BAS) and Computer Supported Cooperative Work (CSCW) is recommended.

Lecturer

Description

Business Intelligence is “a broad category of applications, technologies, and processes for gathering, storing, accessing, and analysing data to help business users make better decisions.” (Watson, 2009, p. 491).

This course provides an introduction to Business Intelligence including related concepts such as data structures, data warehousing and data management, the technical BI infrastructure, data warehouses, data lakes, big data and ETL processes. The focus of the course is on collaboration systems and on the application of Social Collaboration Analytics, an approach for analysing collaboration activities in Enterprise Collaboration Systems (Schwade, 2021).

Upon completion of this course, the students will have acquired the following skills:

• Awareness of the different types of data in business software and relations between the data

• Data modelling and data warehousing concepts and technologies

• Data integration

• Application of analytics and reporting and interpretation of results

• Data visualisation

• Practical understanding of Microsoft Power BI

Literature and Material

Relevant literature and lecture documents will be made available electronically in the form of PDFs (and videos) during the semester in the course community on UniConnect (see here).

Exercise

Time/Room

Please note: There is no strict separation of lecture and exercise part. Theoretical and practical parts alternate in the 4-hour slot.

Requirements (recommendation)

• Participation in the lecture BI

Lecturers

Description

The exercise provides an introduction to Microsoft Power BI and provides the students with the basic skills for their practical group work.

Literature and Material

Relevant literature and lecture documents will be made available electronically in the form of PDFs (and videos) during the semester in the course community on UniConnect (see here).

Assessment and Grading

The module grade is a 50:50 composite of two papers (Hausarbeiten):
1. An individual paper submission and
2. a group work (dashboard development) with presentation.

Both examinations must be passed (>= 4.0 or >= 50%) in order to successfully complete the module.

Registration for the module assessment in KLIPS takes place after successful group formation in the first weeks of the semester (further information on this in UniConnect).

Individual work

The individual work is a written research paper on a partial aspect of the topic of the group work and will provide the candidates with the necessary scientific background for their practical work on the dashboard.

Group Work

In the group work (preferably in groups of two students), the candidates work on a special topic relating to the course and develop a BI dashboard (with Microsoft Power BI). Important note: When enrolling into this course, candidates agree to make sure that they have access to a computer on which they can run the software MS Power BI. Power BI is a proprietary software (covered by the licence agreement of the University), which only runs on the Microsoft Windows operating system. The exercise will provide the necessary basic skills for this practical part. The final group presentation will answer selected research questions with the help of the developed BI dashboard.

Credit Points

• Lecture Course (2 SWS): 3 credit points (ECTS)

• Exercise (2 SWS): 3 credit points (ECTS)

• Total (4 SWS): 6 credit points (ECTS)

What do I have to do to participate in the course?

To participate in this course, you should do the following:

1. Apply for participation in this course using the special application form provided by the Business Software Research Group (we will treat your information confidentially). Priority will be given to students who have successfully attended the BSc course on Computer Supported Cooperative Work.

2. Wait for a response e-mail to your application.

In case you have been admitted:

1. Register for the course in KLIPS. Students who intend to take the course must be registered in KLIPS. If you are unable to register in KLIPS, send an E-Mail to the course coordinator (see above) explaining your situation.

2. UniConnect account. Make sure you have a working user account on UniConnect. If you have not already done so, please register. You can find instructions on how to do this here: https://uni-ko.de/reg_instruct_uniconnect
   (Please note that it may take one to two working days from registration to activation of the account).

3. All admitted students who are enrolled for the course in KLIPS will be added to the course community in UniConnect (near to the start of the course) where you will receive further information.

4. Attend the first lecture meeting. The first lecture will take place on-site and all course participants must attend this lecture. The information on the room will be contained in the acceptance e-mail.

Note: The course is taught in compressed mode; all students must attend the first session and there is no possibility for late enrolment after this first meeting.