MET3 Business Data Processing

• Topics

  The purpose of the course is to provide students with practical skills in economic modelling and data analysis, with spreadsheets as a key tool and artificial intelligence as an integrated part of the work processes. The course emphasises formulating, analysing and solving problems in business and economics.

  The course covers the following main areas:

  • Building economic models and analyses in spreadsheets
  • Decision analysis under uncertainty and economic reasoning, with emphasis on technology as a means for better decisions
  • Data handling, transformation and analysis
  • Visualisation and communication of data and analytical results
  • Fundamental understanding of data structure and how it affects analysis
  • Collaboration with artificial intelligence in modelling, analysis and communication

  Throughout the course, students will work with realistic problems, from raw data to analysis and presentation of results.

• Learning outcome

  Upon completion of the course, the student will have acquired the following:

  Knowledge

  • has fundamental knowledge of data processing for business and economics, including how models and assumptions affect analyses and decisions
  • has knowledge of how spreadsheets can be used for economic modelling and analysis
  • understands how data structure affects analytical possibilities
  • has awareness of ethical issues related to data processing, privacy, sustainability, and the use of artificial intelligence
  • has a basic understanding of artificial intelligence and its applications in business and economics

  Skills

  • can build economic models in spreadsheets
  • can process and analyse data from various sources
  • can visualise and communicate analytical results in a convincing manner
  • can use models and analyses to evaluate alternatives and support decisions
  • can apply artificial intelligence in data processing and analysis, and assess when and how AI assistance is appropriate
  • can specify economic problems for analytical modelling, communicate technological needs to technical experts, and critically validate machine-generated results

  General competence

  • can apply knowledge and skills to solve business problems using appropriate information technology
  • can reflect on how artificial intelligence changes work processes and decision support in organisations
  • can collaborate in groups on academic problems and present results orally
  • can assess the quality of their own and others' analyses, and understand the limitations of data-driven and AI-supported decision-making processes

• Teaching

  The course consists of on-campus sessions, instructional videos and in-person group exercises.

• Credit reduction due to overlap

  The course corresponds to MET030. Credit is not awarded for both courses.

• Compulsory Activity

  One individual assignment. 

  One group-based submission of an exam-related case assignment. 

  Approved mandatory activities are only valid in the semester they were achieved.

• Assessment

  Group-based oral exam based on a case assignment (cf. mandatory activities). Individual grading. Group size 3-4 students with a duration of 30 minutes per group.

• Grading Scale

  A-F

• Computer tools

  Microsoft 365 and selected analytical tools

• Literature

  Announced at the start of the semester

• Retake

  Retake in MET3 will not be offered during the non-teaching semester (spring). Only mandatory bachelor courses with an individual written school exam or a home exam lasting up to one day will have a retake assessment in the non-teaching semester.

  For detailed information regarding the retake policy, please visit our website: https://www.nhh.no/en/for-students/examinations/retake-of-exams (copy URL).