Business Analytics

The Business Analytics (BAN) major gives you the quantitative analytical tools necessary for decision-making in today's modern, data-driven economy.

Availability of large amounts of data creates new possibilities and challenges for businesses, and the ability to make good decisions based on big data is a critical factor for survival in the modern economy. Therefore, business analytics skills are in high demand in the modern job market.

In this major you will learn programming and data management, how to use statistical tools to explore and deduct patterns from data, how to use optimization and simulation tools to support better decision-making in practical situations, and how to employ tools like machine learning and artificial intelligence for automated decision support.

You will have the opportunity to learn how to apply analytical tools in a wide range of business contexts such as operations management, finance, accounting and marketing; and in a wide range of industries such as energy, retail and banking. Upon completion of the this profile, you will have the necessary skills to support managerial decision-making in modern companies and communicate with technological experts.

  • Subject areas

    Subject areas

    To attain the necessary skills in business analytics, the compulsory courses in the profile covers the following areas:

    • Programming: Skills to extract, handle and use real-world data for problem solving in business.
    • Data analysis: Statistical learning and predictive analytics for learning and extrapolating from data.
    • Business modelling and prescriptive analytics: Optimization models and simulations for decision support, analysis and improving business processes.

    You can then choose from a wide range of elective courses to gain insight into into a multitude of business applications, and/or choose methodological courses to strengthen your quantitative skills in areas such as machine learning, optimization and forecasting.

  • Structure and recommended tracks

    Structure and recommended tracks

    The compulsory courses provide you with knowledge and skills in the following core areas:

    Programming (7.5 ECTS):

    BAN405 Python Programming for Data Science

    We strongly recommend that you take this course in the first semester as programming skills are needed in later courses.

    Predictive analytics (7.5 ECTS):

    BAN404 Statistical Learning

    Business modelling and prescriptive analytics (15 ECTS):

    BAN402 Decision Modelling in Business

    BAN403 Simulation of Business Processes

    The compulsory courses are recommended to be taken during the first year of the master program.

    The remaining 15 ECTS of the major must be chosen from the list of electives. The list of electives can broadly be divided into two categories. Methodological courses focus on analytical methods, although the methods are often illustrated and applied in specific business contexts.

    Application-oriented courses focus on understanding how value is created in businesses and how analytics can provide better decisions.

    Electives - Business Applications

    BAN425 Applied Risk Management (2,5 ECTS)
    BAN427 Insurance Analytics (2,5 ECTS)
    BAN434 Social and Economic Networks (7,5 ECTS)
    BAN435 Blockchain Technology and Applications (2,5 ECTS)
    BAN439 Detecting Fraud through Textual Analysis (2,5 ECTS)
    BAN440 Data Driven Business Analysis (7,5 ECTS)
    BAN442 From data to value: Machine Learning with Python (2,5 ECTS)

    BAN443 Transforming Business with AI: The Power of Large Language Models (7,5 ECTS) BUS401E Strategic Profitability Analysis (7,5 ECTS)

    BUS401N Strategic Profitability Analysis (7,5 ECTS)
    BUS403 Supply Chain Management (7,5 ECTS)
    BUS429 Pricing Analytics and Revenue Management (7,5 ECTS)
    BUS432 Operation Management (7,5 ECTS)
    BUS465 Detecting Corporate Crime (7,5 ECTS) BUS470 Retail Analytics (7,5 ECTS)
    ECN425 Solving Economic and Social Problems with Big Data (7,5 ECTS)
    ECN431 Data Driven Business Analysis (replaced by BAN440) (7,5 ECTS)
    ECN435 Data-Driven Public Policy (7,5 ECTS)
    ENE431 Shipping Economics and Analytics (7,5 ECTS) ENE434 Energy Industry Analytics-(7,5 ECTS)
    FIE453 Big Data with Applications to Finance (7,5 ECTS) MBM433 Customer Analytics in a Digital World (7,5 ECTS)
    MBM436 Strategic Marketing Analytics for Digital Businesses (7,5 ECTS STR453 Digitalization-(7,5 stp)

    Electives - Methodological Courses

    BAN437 Uncertainty in Optimization (2,5 ECTS)
    BAN423 Benchmarking with DEA, SFA, and R (2,5 ECTS) BAN426 Applied Data Science (2,5 ECTS)
    BAN430 Forecasting(7,5 ECTS)
    BAN432 Applied Textual Data Analysis for Business and Finance (7,5 ECTS)
    BAN436 Introduction to Python (2,5 ECTS)
    BAN438 Application Development in Python (7,5 ECTS) BAN441 Introduction to the use of spatial data (2,5 ECTS)
    ECN430 Empirical Methods and Applications in Macroeconomics and Finance (7,5 ECTS)
    ECO401 Optimisation and Microeconomic Theory (7,5 ECTS)
    STR459 Artificial Intelligence and Robotics (7,5 ECTS)

    Master Thesis

    BANTHE Independent work/thesis in Business Analytics (30 ECTS)

  • Learning outcomes

    Learning outcomes

    Upon successful completion of the major, the candidates shall

    KNOWLEDGE

    K1: Have a solid knowledge about relevant methods from statistics and business modelling

    K2: Have in-depth and up-to-date knowledge on how to use data to support decision-making in business

    K3: Understand business analytics articles published in international scientific journals and formulate relevant research questions

    SKILLS

    S1: Build and solve decision models for real-world business problems

    S2: Bring together decision modelling and data analysis for practical business applications

    S3: Be proficient in computer programming in order to write code for business analytics problems and to communicate well with software developers

    GENERAL COMPETENCE

    G1: Solve business analytics problems in teams with people from different backgrounds

    G2: Reflect on the ethical challenges specific to business analytics

    G3: Contribute innovative solutions for business analytics problems and communicate them to executives and other stakeholders

  • Empirical methods courses

    Empirical methods courses

    The compulsory courses cover this requirement.

  • Ethics, Responsibility and Sustainability (ERS)

    Ethics, Responsibility and Sustainability (ERS)

    You are required to take at least 7.5 ECTS in Ethics, Responsibility and Sustainablity (ERS). You can choose any course at NHH’s list of ERS courses. You can choose whether to fulfill the ERS requirement within your major, or as part of your minor, or as one of your elective courses.

    None of the ERS courses are included in the BAN major, and you will need to fulfill this requirement as one of your elective courses or as part of a minor.

    Read more about ERS courses

  • Sustainability

    Sustainability

    The courses ENE434 Energy Industry Analytics and BUS401 Strategic Profitability Analysis treat sustainability issues. ENE434 studies, among other things, how to analyze changes in market structure caused by changes towards low-carbon technologies and other changes in regulations. BUS401 includes insights from behavioral studies on the importance of accounting for sustainability in decision-making processes.

  • International opportunities

    International opportunities

    As an NHH student you have excellent opportunities to gain valuable international experience during your studies through semester exchange, the Double Degree programme, CEMS, Engage.EU, Intern Abroad and summer courses. Note particularly our double degree partner Ivey School of Business which offers many interesting courses in Business Analytics as well as in other fields.

    Read more about international opportunities

  • Career

    Career

    This major is suitable for those seeking jobs as analysts, either in companies or as consultants, and in general to all those seeking to complement their business background with analytical skills to succeed in the modern data-driven environment. A thorough understanding of business analytics will also enable you to communicate with technological experts and be useful for digital strategy managers.

    Read more about career possibilities for NHH graduates

  • Minor

    Minor

    COURSES IN BUSINESS ANALYTICS (BAN) MINOR

    To take Business Analytics (BAN) as a minor, you need 22.5 ECTS from the profile’s portfolio of courses.

    AT LEAST ONE OF THESE

    BAN405 Python Programming for Data Science (7,5 ECTS) BAN402 Decision Modelling in Business (7,5 ECTS)
    BAN403 Simulation of Business Processes (7,5 ECTS) BAN404 Statistical Learning (7,5 ECTS)

    ELECTIVES

    BAN400 R Programming for Data Science

    BAN423 Benchmarking with DEA, SFA, and R (2,5 ECTS)
    BAN424 Applications of Business Analytics (not offered) (2,5 ECTS) BAN425 Applied Risk Management (2,5 ECTS)
    BAN426 Applied Data Science (2,5 ECTS)
    BAN427 Insurance Analytics (2,5 ECTS)
    BAN430 Forecasting (7,5 ECTS)
    BAN431 Econometrics and Statistical Programming (expired) (7,5 ECTS)
    BAN432 Applied Textual Data Analysis for Business and Finance (7,5 ECTS)
    BAN433 Applied Cloud Computing for Enterprises (not offered) (2,5 ECTS)
    BAN434 Social and Economic Networks (7,5 ECTS)
    BAN435 Blockchain Technology and Applications (2,5 ECTS) BAN436 Introduction to Python (2,5 ECTS)
    BAN437 Uncertainty in Optimization (2,5 ECTS) BAN438 Application Development in Python (7,5 ECTS)
    BAN441 Introduction to the use of spatial data (2,5 ECTS)
    BAN442 From data to value: Machine Learning with Python (2,5 ECTS)

    BAN443 Transforming Business with AI: The Power of Large Language Models (7.5 ECTS)
    BUS429 Pricing Analytics and Revenue Management (7,5 ECTS)
    ECN430 Empirical Methods and Applications in Macroeconomics and Finance (7,5 ECTS)
    FIE453 Big Data with Applications to Finance (7,5 ECTS)
    FIE458 Deep Learning with Applications to Finance (7,5 ECTS)
    STR459 Artificial Intelligence and Robotics (7,5 ECTS)