Big Data Analytics

  • Duration: Full semester
  • Spring semester , Exchange student
  • ECTS 7,5 ECTS
  • Application period Application deadline: 15 October

Big Data Analytics (ØKA2013) is a 7,5 ECTS course in the spring semester on Bachelor level. A 2-day home exam finalizes the course. The course is only open to exchange students from our partner institutions. 

To view possible course combinations, view "About the course".

About the course

Possible course combinations

Please be aware that this is a new course. We will check if the courses can be combined with the following courses. Information will be updated. 

Course time schedules

The course time schedule will be published after:

  • 01 December for the following spring semester

Required prerequisites:

  • Course in statistics

Course material

To view the course material for ØKA2013 Big Data Analytics, please search  here. Do notice that the overview might not be available until a few weeks before the official semester start.

Course content

  • Definitions of big data analytics
  • Application areas of big data analytics
  • The business value of big data (value chain)
  • Databases for big data analytics
  • Data mining and data analytics
  • Data visualization
  • Big data architectures
  • Case studies: Application of relevant software to solve real-life, big data business problems

Learning outcomes

Upon completion of the course, the student shall have obtained the following learning outcomes:


The student

  • can define what big data sets are based on the most commonly used definitions
  • can refer to various application areas of big data analytics
  • can describe how big data can be transformed into business value
  • can present the architecture of big data
  • can explain (in own words) how various techniques for analyzing big data sets work in practice  
  • can explain important issues related to privacy and ethical issues in the use of big data


The student

  • can structure the process of performing big data analytics
  • can apply basic techniques for gathering, storing, distributing, and processing big data sets
  • can analyze relevant big data sets using appropriate analytical frameworks and software from various industries/areas including (but not limited to):
    • Accounting
    • Asset pricing / Trading / Banking
    • Entertainment industry
    • Sales
    • Etc.

General Competence

The student

  • can take part in the planning- and implementation of big data projects

Teaching and working methods

Lectures (live and video), workshops with case studies, problem-solving, mandatory hand-ins.

Coursework requirements

Written and oral mandatory coursework. 


Two days take home exam. 

Practical information


On-campus housing is eligible for students applying for a full semester/academic year.

General information on accommodation at Campus Lillehammer.

What does it cost?

Free for exchange students

Study start information

An Orientation Week is arranged in the first week of the spring semester. Most lectures are expected to begin the same week.

Would you like to apply?

The course is available only for students coming from our partner institutions. Contact the International Coordinator at your home institution to find out if you are eligible for exchange studies at Inland Norway University of Applied Sciences (INN University). Please notice that applications can be submitted for one campus only.

Application procedure and documents