Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
LEARNING OUTCOMES
The objective of the course is to give the students an understanding of the data informed decision-making. The focus is on business-oriented analytical skills, which enable the students to work with the data, to understand them and turn them into intelligence and actions.
Credits: 6
Schedule: 25.02.2019 - 10.04.2019
Teacher in charge (valid 01.08.2020-31.07.2022): Yong Liu
Teacher in charge (applies in this implementation): Yong Liu
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
This course aims at providing an understanding of issues related to data informed decision-making and problem solving. To do this, it offers a balanced insight into the building blocks of business intelligence (BI), such as data management, data warehousing, reporting, and analytics. Besides a set of guest speakers representing academia and business life, a central feature of the course is a BI challenge, which students work in small groups. The course requires both independent learning skills and organizational skills.
Assessment Methods and Criteria
Valid 01.08.2020-31.07.2022:
Spring 2021:
50% assignments
50% learning diarySpring 2022:
70% assignments
30% learning diary
Workload
Valid 01.08.2020-31.07.2022:
Contact teaching 24h
Independent work 136h
Total 160h (6 ECTS)
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
Course book: Sharda, Ramesh Delen, Dursun Turban, Efraim (2014) Business Intelligence and Analytics (10th edition). Pearson, New York (NY).
Substitutes for Courses
Valid 01.08.2020-31.07.2022:
37E00550 Business Intelligence
EMS MIM students can replace this capstone with 42E05400 CEMS Business Project
Prerequisites
Valid 01.08.2020-31.07.2022:
Before registration, one is expected to know SQL and database management basics.