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ØKA2013/1 Big Data Analytics


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


  • Definitions of big data analytics
  • Application areas of big data analytics
  • 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

Arbeids- og undervisningsformer

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

Obligatoriske krav som må være godkjent før eksamen kan avlegges

Written and oral mandatory coursework. 


Two days take home exam.