Master of Science in Data Science for Business
The goal of this programme is to create specialists in the domain of data analytics to support business strategy and decisions of the firm.
What
The goal of this programme is to create specialists in the domain of data science to support business decisions of the firm. As a result, the profile of a typical DS4B graduate consists of three cornerstones:
- analytical mindset with a strong interest in data;
- hands-on experience that can readily be applied in business;
- the ability to translate complex decision support models to a business environment.
The programme has been training students since 1999, which makes it the longest-running (predictive) analytics programme in the world. The programme addresses the needs of companies for better-educated staff with strong skills in the domain of analytical customer relationship management and business analytics. Thanks to information technology and the availability of market data both at the demand side (customer information, e.g. scanning data …) and supply side (internal information about marketing actions, competitors, production data, ...), data science has become omnipresent in today's business environment. As a result, there is a strong need in the marketplace for people able to: control and cope with the huge amount of available data; and generate and use models to translate these raw data into useful business information. These people will be the interface between company management (e.g. production manager, marketing manager) and the suppliers of data within the organisation. Currently, departments are not facing the problem how to obtain data, but rather how to transform these massive amounts of data into useful information and systems.
At its core, the main methods in this program are related to data mining and machine learning. At first, the students are introduced to a wide range of machine learning techniques. Afterwards, these techniques are applied in real-life business settings in a range of courses. One of the main topics in the program is analytical customer relationships management.
We train students in the theoretical underpinnings but the main focus is on the practical skills of managing customer databases:
- acquisition (identifying and attracting new customers);
- cross/up-selling (profitable usage stimulation);
- retention (identifying customers who intend to attrite/churn and trying to keep profitable customers);
- recapturing ‘lost’ customers.
Next to the business content, a big focus is on computer programming. Students will become expert programming in the following open-source programming languages: Python, R, SQL and (Py)Spark. The programme also includes specific courses on social media and web analytics, prescriptive analytics, and big data (Hadoop, Spark) technology.
We also added a Deep Learning and a Machine Learning course to the mandatory courses. This significantly ups the methodological part of the programme. It requires prospective students to review their math skills (derivatives, gradient, hessian ...). Several advanced topics are covered such as natural language processing, deep learning, and reinforcement learning. Several of these methods are applied to various business problems such as credit scoring, fraud detection, HR analytics, demand forecasting, among others.
For whom
The admission requirements depend on prior education (type of degree, country of issue etc ...) or additonal experience.
In addition we require candidates to:
- score very high on an online statistics test (link to be found on our website: www.mma.ugent.be)
- have followed an R programming course (e.g. a freely available online course) and demonstrate their ability to use the language
Structure
All students follow the same mandatory course schedule detailed on our website. From April on, all course work is suspended to fully concentrate on the project.
Master's dissertation
The Master's dissertation consists of a real-life project for a company dealing with a specific marketing issue. A list of previous projects can be obtained from: www.ugent.be/eb/nl/opleidingen/master-na-master/master-of-science-in-data-science-for-business
Labour Market
The choice of engaging in a specific advanced master’s programme is, even more than a master’s programme, related to the question: “Which job(s) will I be trained for?”. Fortunately, there is a broad variety of jobs for which students are trained. About equal proportions of DS4B graduates are currently working in different areas of Business Analytics. Our graduates have made important contributions in the business world; at least two are CEOs of sizeable organisations. Fifteen MScMA graduates have pursued academic research careers and completed their PhDs (+ five are currently in progress). Five graduates have become analytics (assistant/associate/full) professors. In order to offer potential students more insights into the variety of functions, companies, industries, and even countries where our graduates are already present, some former students were very willing to share their experiences in this programme with – possibly – their future colleagues … Their testimonials can be found at www.mma.UGent.be/mma.pdf (see middle section).
Quality Assurance
At Ghent University, we strive to educate people who dare to think about the challenges of tomorrow. For that purpose, we provide education that is embedded in six strategic objectives: Think Broadly, Keep Researching, Cultivate Talent, Contribute, Extend Horizons, Opt for Quality.
Ghent University continuously focuses on quality assurance and quality culture. The Ghent University's quality assurance system offers information on each study programme’s unique selling points, and on its strengths and weaknesses with regard to quality assurance.
More information:
Unique Selling Points
- Analytical mindset with a strong interest in data: the backbone of business analytics is a sufficient volume of high-quality data. Unfortunately, data are seldom readily available; data scientists must collect and integrate data across different sources and systems. Advanced analytical skills are necessary to extract relevant information from the data.
- Hands-on experience that can be readily applied in business: an MScDS4B graduate is different from the typical graduate of an advanced Master’s programme in artificial intelligence or statistics/data analysis. The MScDS4B programme focuses on how to apply advanced methods to business problems, rather than on the theoretical properties of advanced analytics tools.
- The ability to translate complex marketing decision models to a business environment: higher-level managers often struggle to grasp the results of analytics tools, while technicians lack a strong comprehension of the business problems that need to be solved. The MScDS4B programme strives to deliver graduates that can bridge this gap. Presentations are the teaching method used to train graduates in this skill.
- Pioneering role: the Master of Science in Marketing Analysis (in 2020 renamed DS4B) was the first (in 1999) to start an advanced Master’s Programme in Predictive Analytics worldwide. We have the ambition to continue to lead the way in introducing new methodologies to solve complex marketing decision problems.
Strengths
- The programme has a strong vision (cf. supra: unique selling points) and a pioneering role, acknowledged by alumni (competitive advantages), resulting in graduates easily finding jobs (on average after 1.5 months).
- The Master’s dissertation consists of a real-life business project, which provides experience in a professional context and is partially externally assessed.
- An active feedback culture speeds up the learning process and applies both to individuals and groups.
- A wide variety of assessment methods is used, tailored to the unique selling points mentioned above. Open-book exams are used to mimic real-life situations.
- There is a strong focus on presentations (readily available and business- minded graduates)
Challenges
- Cooperation with companies is getting harder (is this due to the COVID-19 crisis? Stricter (EU) regulations regarding data governance?)
- The administrative processes for admission are slow: responsiveness could be increased.
- Students have no options to tailor the content of the program
This study programme is accredited by the Accreditation Organisation of the Netherlands and Flanders (Dutch: NVAO). Accreditation was extended following the positive outcome of the institutional review in 2022. Programme quality was validated by a quality review, i.e. a screening of the Education Monitor by the Education Quality Board. The Quality Assurance Resolution (in Dutch) can be found here.
This program is accredited by AACSB International – The Association to Advance Collegiate Schools of Business. AACSB is a global nonprofit association whose accreditation processes are ISO 9001:2015 certified.
This information was last updated on 19/12/2023.
In case of questions or suggestions with regard to the publicly available information, please contact the study programme.