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2020/2021  MA-MMBFO2001U  Analytics and Big Data

English Title
Analytics and Big Data

Course information

Language English
Course ECTS 2 ECTS
Type Mandatory
Level Part Time Master
Duration One Quarter
Start time of the course Autumn
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for Full-Time MBA
Course coordinator
  • Dolores Romero Morales - Department of Economics (ECON)
Main academic disciplines
  • Information technology
  • Marketing
  • Statistics and quantitative methods
Teaching methods
  • Face-to-face teaching
Last updated on 10-06-2020

Relevant links

Learning objectives
  • Understand the use of Regression Analysis in Decision Making, such as in Business Forecasting
  • Understand the use of Optimization in Decision Making, such as in Portfolio Optimization
  • Understand the use of Risk Analysis in Decision Making, such as in Financial Investment
  • Understand the use of Decision Analysis in Decision Making, such as in Project Management
  • Appreciate the implications of uncertainty in Decision Making and the need for flexible and robust solutions
  • Understand the potential Big Data has for different industries and different departments in the organization
Examination
Analytics and Big Data:
Exam ECTS 2
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 10 pages
Assignment type Written assignment
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) Internal examiner and external examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content, structure and pedagogical approach

In the current competitive environment, being able to extract value from business data is both a crucial skill for individuals and a main source of competitive advantage for firms. This includes understanding the relationships between different business factors, forecasting trends, appreciating the risks arising from management actions, and optimizing investment strategies. Decisions are often taken under considerable uncertainty and time pressure. Therefore, managers need to be able to grasp the range of uncertainty rapidly and make rational decisions, which are both flexible and robust. This course aims to enhance your ability to apply modern Analytics tools to decision-making. It is a practical course, which uses computer software to illustrate how to apply the methodologies introduced. Extensive use will be made of the popular spreadsheet software, Excel. The course is multidisciplinary with links to accounting, economics, finance, marketing and operations management.

Description of the teaching methods
The lectures will be based on texbook readings, articles, cases and a high level of student participation.
Feedback during the teaching period
During the teaching period, one-to-one feedback will be provided during the workshops and the office hours.
Student workload
Teaching 24 hours
Preparation 20 hours
Examination 15 hours
Last updated on 10-06-2020