Business analytics is the application of quantitative analytical tools for the purpose of value creation in business.
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 in order 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 to practical decision making situations in operations management, marketing and pricing, finance, accounting, and auditing, and you will also develop your communicative and collaborative skills by participating in team projects and by presenting your findings.
The major broadly covers the following areas:
- Programming skills for data handling and problem solving in business.
- Data analysis. Statistical learning and predictive analytics for learning and extrapolating from data.
- Business modelling and prescriptive analytics. Using optimisation models and simulations for decision support, analysis and improving business processes.
Upon successful completion of the major, the candidates shall
K1: Have a solid knowledge about relevant methods from statistics and operations research
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
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
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
The compulsory courses provide you with knowledge and skills about the following core areas:
- Programming (7.5 ECTS). A minimum requirement is BAN401 (7.5 ECTS), or BAN420 (2.5 ECTS) in combination with two other approved 2.5 ECTS programming courses (current list: BAN421, BAN422). We strongly recommend that you take the introductory courses in R programming, BAN401 or BAN420, in the first semester. This skill is needed in later courses.
- Predictive analytics (7.5 ECTS). You can choose between BAN404 or FIE453. It is possible to take the other one, the one not chosen as a core course, as an elective.
- Business modelling and prescriptive analytics (15 ECTS). You will learn how to use optimization models for decision support (BAN402) and how to use simulation to analyze and improve business processes (BAN403).
The remaining 15 ECTS of the major must be chosen from the list of electives.
Recommended course combinations
Recommended course combinations
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.
- BAN401 Applied programming and data analysis for business
- BAN404 Predictive analytics with R
- FIE453 Big Data with Applications to Finance
- BAN420 (2.5 ECTS) Introduction to R
- BAN421 (2.5 ECTS) Data structures in R
- BAN422 (2.5 ECTS) Visualization with R
- BAN430 Forecasting
- BAN423 (2.5 ECTS) Benchmarking with DEA, SFA and R
- BAN426 (2.5 ECTS) Applied Data Science
- BAN432 (FIE452) Applied Textual Data Analysis for Business and Finance
- ECO401 Optimisation and Microeconomic theory
- ECN430 Empirical Methods and Applications in Macroeconomics and Finance
- STR459 Kunstig intelligens og robotisering
- BAN402 Decision modelling in business
- BAN403 Simulation of business processes
- BAN424 (2.5 ECTS) Applications of Business Analytics
- BAN425 (2.5 ECTS) Applied Risk Management
- BAN427 (2.5 ECTS) Insurance Analytics
- BUS403 Supply Chain Management
- BUS427 Advanced Management Accounting
- BUS429 Pricing Analytics and Revenue Management
- BUS432 Operasjonell planlegging/Operations management
- BUS460 Operational Risk Management
- ECN431 Applied Data Analysis of Firm Strategy and Competition
- MRR453 Digital Auditing
- BUS401 Strategiske lønnsomhetsanalyser og prising
- STR453 Digitalisering
- BUS465 Corporate Crime: Detection and Prevention
Empirical methods courses
Empirical methods courses
The compulsory courses cover this requirement.
All ethics courses approved by NHH are allowed.
As an NHH student you have excellent opportunities to gain valuable international experience during your studies through exchange programmes, the CEMS Master's in International Management (MIM) joint degree and summer courses.
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.