Data Science for Business & Commerce
Niveau
Master's course
Learning outcomes of the courses/module
The following skills are developed in the course:
- Students know the basic application areas of data collection, data storage, data analysis and data use in the context of business-related applications.
- Students understand the special challenges of this field of application and are familiar with established best practice methods in this area.
- Students are also able to design and implement data-based applications in this area themselves, taking into account domain-specific requirements.
- Students know the basic application areas of data collection, data storage, data analysis and data use in the context of business-related applications.
- Students understand the special challenges of this field of application and are familiar with established best practice methods in this area.
- Students are also able to design and implement data-based applications in this area themselves, taking into account domain-specific requirements.
Prerequisites for the course
3rd semester: No prerequisites
Course content
The following content is discussed in the course:
- CRM on the strategic level
- CRM in process management
- CRM on the operative level (CRM software systems)
- Operative CRM
- Analytical CRM
- Communicative CRM
This course is offered as an elective course together with the Master's Course in Web Communication and Information Systems.
- CRM on the strategic level
- CRM in process management
- CRM on the operative level (CRM software systems)
- Operative CRM
- Analytical CRM
- Communicative CRM
This course is offered as an elective course together with the Master's Course in Web Communication and Information Systems.
Recommended specialist literature
PRIMARY LITERATURE:
- Cady, F. (2017): The Data Science Handbook (Ed. 2), Wiley, Hoboken (ISBN: 978-1119092940)
SECONDARY LITERATURE:
- Meier, A.; Stormer, H. (2012): eBusiness and eCommerce: Management der digitalen Wertschöpfungskette (Ed. 3), Springer, Berlin (ISBN: 978-3-642-29801-1)
- Cady, F. (2017): The Data Science Handbook (Ed. 2), Wiley, Hoboken (ISBN: 978-1119092940)
SECONDARY LITERATURE:
- Meier, A.; Stormer, H. (2012): eBusiness and eCommerce: Management der digitalen Wertschöpfungskette (Ed. 3), Springer, Berlin (ISBN: 978-3-642-29801-1)
Assessment methods and criteria
Seminar thesis
Language
English
Number of ECTS credits awarded
4
Share of e-learning in %
30
Semester hours per week
1.75
Planned teaching and learning method
The following methods are used:
- Lecture with discussion
- Interactive workshop
- Case studies
- Lecture with discussion
- Interactive workshop
- Case studies
Semester/trimester in which the course/module is offered
3
Name of lecturer
Mag. Johannes Spiess
Academic year
Key figure of the course/module
MDS.5
Type of course/module
integrated lecture
Type of course
Compulsory
Internship(s)
none