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With the digitalization of enterprise information systems, the proliferation of internet and the widespread use of mobile devices and sensor technology, the amount of data stored in systems has grown enormously. Simultaneously, high speed CPU and fast massive memory enable new business analytics, like web analytics, text mining and social network analysis.
After completing this course, you will be able to:
- Explain the main trends in business analytics;
- Assess new IT developments from a business value perspective;
- Calculate the value of information (the information gain) in simple cases.
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The course consists of lectures, lab sessions, guest lectures and a group paper assignment. Topics covered in the lectures include:
- Creating value with big data;
- Information theory;
- Text mining, social network analysis;
- Smart auditing, process mining;
- High-performance data processing;
- Responsible data science
For each lecture, you have to read some scientific articles or other background material. The lab part is mainly by self-study and introduces you to process mining and to the programming language Python (not for students Data Science & Society). In addition, guest lectures will provide insight in practical applications in e.g. auditing, marketing and logistics. Students from Data Science & Society have to write a group paper that gives a critical evaluation of the application of business analytics in some business domain.
Type of instructions
Lectures, self-study, lab sessions and guest lectures
Type of exams
Written exam (80%) and assignment: Group paper (DS&S) OR Python lab (20%),
Specifics
The result of the assignment is not transferable to the next year.
Students are expected to have a basic level of Statistics, or to acquire that with selfstudy in the first weeks.
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