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Data Science for Business & Commerce
level of course unit
Master's courseLearning outcomes of course unit
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 and co-requisites
3rd semester: No prerequisites
course contents
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 or required reading
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 of instruction
Englishnumber of ECTS credits allocated
4eLearning quota in percent
30course-hours-per-week (chw)
1.75planned learning activities and teaching methods
The following methods are used:
- Lecture with discussion
- Interactive workshop
- Case studies
- Lecture with discussion
- Interactive workshop
- Case studies
