Corvinus is the first in the country to launch a course in data science in business. By launching the degree programme, the university is responding to corporate needs, as a number of major companies and consultancy firms have indicated a need for professionals who can extract valuable information and knowledge from corporate data.
“Companies recognised that they have a large amount of data that needs to be exploited. This is typical not only for consultancy firms, but also for any company, e.g., Corvinus has a joint project with LEGO on data modelling and data analysis,” says Ildikó Borbásné Szabó, programme director.
Combining mathematical, IT and business knowledge
To apply for the degree programme, you need to have an advanced level GCSE in mathematics, as the degree programme is based on strong mathematical knowledge. “To be able to analyse these data and find correlations, you need to have a very good mathematical-statistical methodological background,” says the programme director. “We also build on IT skills, as these tasks require not only methodological but also practical knowledge.”
As a data scientist, the primary need is to find data-driven answers to the questions of the company, so business knowledge is also important in this area. “Business data science is different from other programmes, because it relies heavily on these three legs, namely mathematical-methodological, IT and business knowledge,” says Ildikó Borbásné Szabó.
An advanced-level GCSE is required only in mathematics, IT is not a prerequisite. “The student doesn’t need to come with programming skills, just an open mind about IT. If they liked IT in secondary school and want to work with IT systems or programming languages, I can clearly recommend the degree programme,” says the programme director.
In the very first year, there will be an introduction to data science and programming where, among others, students learn the basics of Python programming. In each subjects a key objective will be to introduce methodological and practical knowledge to students through real-life examples from companies.
Unlike other bachelor’s degree programmes, the data science in business programme is not 6 or 7, but 8 semesters long, which the programme director explains with the strong foundation and broadening of horizons. Separate semesters are planned-e.g., for study abroad and internship. “We would like our students to look at other universities and benefit from the knowledge they obtain there. On the other hand, they will have a dedicated semester working in a specific company, so they will really get practical knowledge and a broader perspective during the training.”
Quick employment and high starting salaries with a degree in data science in business
Business data scientists are already highly sought after, at profession.hu job portal, e.g., searches for ‘analyst’, ‘data scientist’ or ‘data analyst’ will result in more than a thousand job ads. Self-funded training can also be a good investment because of the speed of finding a job even with the help of student loan, because it pays off quickly owing to the acquired knowledge and the expected high starting salaries.
In addition to the English language subjects and the semester abroad, they want to attract internationally renowned lecturers, but they also welcome international students, so the degree programme is a good opportunity to build global contacts. Partner companies include several multinational companies, e.g. LEGO, Starschema or SAP, students can meet them in case studies and project work, and may even offer direct job opportunities.
There are also examples of people starting their own company as data analysts or business information specialists. Neticle is a good example, where they are working on opinion analysis, text mining and similar methods. The successful company was founded by Péter Szekeres, who studied at Corvinus.
In addition to finding a job, a master’s programme may also be a good option, with three areas of study that allow students to pursue three different paths. They can choose from master’s programmes of Corvinus with a focus on economics, but they can also deepen their knowledge in IT or mathematics.
How do data create value for business?
The process of corporate data analysis starts with understanding the business. If we take the example of a music streaming platform, Spotify, the first step is for the company to recognise that it has a database with a lot of songs, and that the songs have individual features. Like any company, they want to make sure that listeners, i.e. their customers, are as loyal as possible to the company, and they want to use the data available to them.
The next step is to extract and understand the data, which requires knowledge of data science methodology. E.g., it is possible to filter by artist or genre, but it is also possible to build on users’ habits, e.g., favourite music and current trends too, and these data blocks need to be extracted, processed and organised into a single database, which requires IT skills. Then, the database needs to be cleansed, missing data need to be dealt with and the data need to be prepared for building models and algorithms.
Spotify, e.g., uses three such models, according to an article published recently. With the collaborative filtering, they define the common interests, and with the help of sound models, they examine the similarities between musical tracks. In addition, texts on social media are analysed using natural language processing algorithms. “These are essentially based on mathematical-statistical knowledge, which then has to be made executable by computer, and this is where IT knowledge with programming languages or even artificial intelligence will be needed,” – the head of the programme explains.
The cycle ends with the company assessing whether the product serves the original purpose and incorporating this into its business processes, which is where business knowledge becomes relevant. “At Spotify, e.g., this is how a personalised playlist is created, allowing the company to offer a value-added service. This is a major contribution to becoming the streaming platform with the largest market share”.
The main goal is to turn data into real value
In addition to professional knowledge, broadening horizons also involves ethical issues. “It is also important these days that data collection is both legally compliant and ethical. In addition, companies using machine learning algorithms may also have ethical issues, and we intend to include these too in the training”.
Project subjects are also planned for the programme where students can work in teams to improve e.g. their communication skills, or intercultural understanding with international students.
Values and value creation are therefore a priority in the education of business data science. “When we talk about producing something from data, it is not going to be an end in itself, it is really going to be an answer to some practical problem,” says the head of the programme. “Whether we are talking about climate change or other social, economic or business challenges, we need to analyse large amounts of data to come up with good answers. This is how we can turn data into value.”
Author: Máté Kovács (Corvinus Communication)
This article was written using the speech recognition app Alrite.