Business Intelligence
Business Intelligence (BI) bridges the gap between modern data science and business applications by transforming data into insights that enable strategic business decision-making. The MSc in Economics and Business Administration – Business Intelligence takes a data-driven approach to solving business problems by focusing on:
- extracting and analysing information from data to predict behaviour and recognise natural patterns
- visualising and presenting results to support managerial decision-making.
The BI programme aims to prepare the students to use a variety of state-of-the-art data analytics tools and apply data science to solve the complex and interdisciplinary challenges that businesses face. During the BI programme, the students will work with data-driven business projects such as:
- Generative AI for Customer Service: Build a chatbot using open-source language models that can handle common customer inquiries in the retail industry, potentially reducing response times.
- Fraud Detection in E-Commerce: Implement machine learning algorithms to detect unusual purchasing patterns, potentially preventing fraudulent transactions in online stores.
- Data-Driven Business Development for Healthcare: Develop predictive models to forecast patient inflow in hospitals, enabling efficient staff and resource allocation.
- Visual Analytics for Sales Managers: Build interactive dashboards that analyse sales data, helping managers forecast trends, identify underperforming regions, and optimise resource allocation.
- AI Adoption in Hospitality: Guide hotels in deploying AI solutions for automating room bookings, feedback collection, and optimising housekeeping schedules.
- Recommender Systems for Media: Develop algorithms that suggest movies or series to subscribers of a streaming platform based on their viewing history.
- Customer Analytics in Retail: Implement clustering techniques to segment customers of a fashion brand, predicting inventory needs for different locations based on regional preferences.
- ECTS transcript – If you are still completing your Bachelor’s degree, upload an ECTS transcript showing the subjects you have studied, your grades, and the number of credits awarded. Your Bachelor’s diploma must be uploaded later, as soon as you receive it.
- Bachelor’s diploma – If you have already graduated, upload your Bachelor’s diploma. A separate ECTS transcript is not required.
Note: Your Bachelor’s degree must be in the same or a related field as the Master’s programme you are applying for. The university will check whether you have completed enough relevant subjects and ECTS credits.
Important! View the full requirements on the university’s official website. Requirements may vary depending where you completed your bachelor education.
Applicants have to prove their English language skills either by an internationally recognized language test or upon previous studies. Usually English language skills can be proved by the following documents:
- TOEFL iBT*
- IELTS Academic
- A Cambridge English qualification
- Higher education degree completed in English
- Secondary education completed in English in a country or school qualification accepted by the university
- An English subject and grade on your secondary school leaving certificate that meet the university’s requirements
- Other
Important: Accepted methods and minimum results depend on study programme and the country where you completed your education. Check the official requirements for your chosen study programme.
*Use the Kastu promo code LTU1000102 when registering for TOEFL iBT and receive a 5% discount.
Graduates who complete the Business Intelligence programme acquire analytical and quantitative skills that are highly demanded by both the public and private sector. BI graduates take up positions in international or Danish companies, public institutions, and consulting firms as BI consultants, data scientists, data engineers, advanced data analysts, machine learning developers, or product owners. After a few years on the labour market, many BI graduates advance to senior data specialist roles (senior data scientist, senior automation engineer, etc.) or managerial roles (BI lead, head of AI, etc.).
