Information on individual educational components (ECTS-Course descriptions) per semester | |
| Degree programme: | Bachelor International Business Administration Part-time |
| Type of degree: | FH Bachelor´s Degree Programme |
| Part-time | |
| Summer Semester 2024 | |
| Course unit title | Big Data |
| Course unit code | 025008042215 |
| Language of instruction | English |
| Type of course unit (compulsory, optional) | Elective |
| Semester when the course unit is delivered | Summer Semester 2024 |
| Teaching hours per week | 2 |
| Year of study | 2024 |
| Level of course unit (e.g. first, second or third cycle) | First Cycle (Bachelor) |
| Number of ECTS credits allocated | 3 |
| Name of lecturer(s) | Eric KYPER |
| Prerequisites and co-requisites |
None |
| Course content |
|
| Learning outcomes |
Data is commonly referred to as the "oil of the 21st century". In many cases, the use of data is a source of significant earnings potential and competitive advantages. At the same time, a data architecture that is accessible from the outside harbours considerable dangers and risk potential. For students of all majors, not only for those in Digital Management and IT, this course provides the foundations to recognise and use the entrepreneurial potential of Big Data and to manage the associated risks. Students will recognise general data mining techniques. They recognise threats to business security and identify business continuity requirements and backup plans in case of data loss. Students understand the primary objectives of Big Data and the associated potential benefits. Students will be able to perform a cost / benefit analysis of big data systems. |
| Planned learning activities and teaching methods |
Interactive course with lecture, case studies, exercises in individual and group work, presentations and homework. |
| Assessment methods and criteria |
Pre-assignment, participation during the seminar in the form of contributions and short presentations (individual or group assignments), post-assignment, individual weighting as determined by the instructors, announcement at the beginning of the semester |
| Comment |
None |
| Recommended or required reading |
Bhasin, M. L. (2006). Data Mining: A Competitive Tool in the Banking and Retail Industries. The Chartered Accountant, 588-594. Bialik, C. (2013, March 1). Data Crunchers Now the Cools Kids on Campus. The Wall Street Journal. Seifert, J. W. (2008). Data Mining and Homeland Security: An Overview. CRS Report for Congress. Stein, J. (2011, March 10). Data Mining: How Companies Now Know Everything About You. |
| Mode of delivery (face-to-face, distance learning) |
Classes with compulsory attendance |
| Summer Semester 2024 | go Top |