2018/2019 BA-BDMAO1002U Digital Technologies and Data-Driven Business
English Title | |
Digital Technologies and Data-Driven Business |
Course information |
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Language | English |
Course ECTS | 15 ECTS |
Type | Mandatory |
Level | Bachelor |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Study board |
BSc in Digital Management
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Course coordinator | |
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Teaching methods | |
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Last updated on 17-08-2018 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||
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Prerequisites for registering for the exam (activities during the teaching period) | ||||||||||||||||||||||||
Number of compulsory
activities which must be approved: 3
Compulsory home
assignments
To enter the examination, the student must have passed three individual mandatory assignments (approved/not approved). Those students who submit and achieve 'not approved' or cannot submit due to illness, will have to submit before a second set date before the end of the course. |
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Examination | ||||||||||||||||||||||||
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Course content and structure | ||||||||||||||||||||||||
Aim of the course The course Digital Technologies and Data-Driven Business constitutes a core foundation course that provides the necessary understanding of digital technologies and the role of data in 21st century businesses and organizations. Course content The growing phenomenon of digitalization brings about profound changes in society and in businesses. Digital technologies and the explosion of data are transforming virtually every aspect of how industries evolve, how businesses deliver value, and how consumers behave. This course investigates the link between the capabilities of digital technologies and the activities and objectives of business organizations. In the course, we examine the technological foundations (systems, software, and databases) of business organizations, and investigate how the capabilities and limitations of digital technologies shape opportunities for business value creation for organizations, entire industries, and society at large. To this effect, we focus on how to develop data-driven solutions in business, by providing skills of extracting value from data through data programming and data analytics. |
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Description of the teaching methods | ||||||||||||||||||||||||
Student centered learning, interactive lectures, in-class exercises, online exercises, case-based teaching. | ||||||||||||||||||||||||
Feedback during the teaching period | ||||||||||||||||||||||||
Students will receive feedback continuously throughout the course from both the teachers and their peers. | ||||||||||||||||||||||||
Student workload | ||||||||||||||||||||||||
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Expected literature | ||||||||||||||||||||||||
TEXTBOOKS
JOURNAL ARTICLES
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