MSc in Data Analytics and Business Economics
Lund, Sweden
MSc
DURATION
1 year
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
STUDY FORMAT
On-Campus
Key Summary
Programme overview
Have you noticed how Netflix and YouTube send you suggestions based on your previous views, or how Spotify makes suggestions based on what you have listened to in the past, or how Amazon shows similar products that you might be interested in based on previous purchases, or how the ads showing on your Facebook page are related to what you purchased or viewed online?
These are companies that are known for their use of 'big data' and analytics to predict and steer customer behaviour. But the truth is that today most organisations are heavily reliant on big data. And the more data businesses amass, the more important it becomes for organisations to be able to harness the information their data provides and use it strategically to improve their operations. This development has given rise to a huge demand for technically talented individuals who can leverage analytics to translate big data into valuable business insights.
In particular, organisations are searching for analytically talented individuals with statistical and programming skills that also understand the business-economic context in which they will be working, as well as the relevant legal and ethical boundaries of that work. The aim of the MSc in Data Analytics and Business Economics is to meet this demand in the labour market.
The programme is multidisciplinary and is designed to solve business problems by integrating statistics, economics, business, informatics and law.
As a student, you will learn how to write your own computer code, how to manage data, how to use statistical machine learning tools in order to explore and deduct hidden patterns from data, and how to incorporate the results obtained into strategic decision-making.
You will also learn about the relevant data legislation, and why it is important to ensure regulatory compliance when working with sensitive data.
You will develop your communicative and collaborative skills. You will learn not only how to work the numbers and draw conclusions, but also how to clearly communicate your results to data technicians and business managers alike.
The programme provides rigorous, hands-on training, and it does so through a careful blend of lectures, seminars, case assignments, computer labs and self-studies.
The training is carried out under the supervision of a number of carefully selected researchers from across the departments of the School, which are working closely together with partner companies and institutions within data analytics in order to maximise the programme’s relevance for employers.
Programme structure
This one-year Master’s degree comprises of 60 credits. The year is divided into two 30 credits semesters.
Semester 1:
Period 1
- Programming in R (3.5 credits)
- Data Visualisation (4 credits)
- Machine Learning from a Regression Perspective (7.5 credits)
Period 2
- Legal Aspects of Data Analytics (4 credits)
- Working with Databases, (3.5 credits)
- Advanced Machine Learning (7.5 credits)
Semester 2:
Period 3
- Analytics-based Strategic Management (7.5 credits)
- Elective (7.5 credits)
Period 4
- Master’s thesis (15 credits)
Career prospects
Transforming data into insights that can enhance decision-making is a key challenge for companies of every size, across all industries.
Be it the travel industry, technology, retail, healthcare, manufacturing, consulting, banking, finance, or insurance, data generated from market interaction is being used to determine and influence trends and gain a competitive edge over other players in the field. Companies are therefore looking for experts who have the capacity to use data to make informed strategic decisions. The same is true in government. Being able to minimise costs while at the same time deliver better services to citizens requires making the most of the information available.
Graduates from the MSc in Data Analytics and Business Economics are at a competitive advantage as organisations are looking for people who are not only fluent in the language of data but who also understand how to apply that data in the business-economic context. This layered skillset enables them to communicate effectively with clients, programmers, managers, data scientists, and policymakers to drive strategic decision-making.