BA Data Science & Business

In business, data is the new oil — it revolutionizes societies and brings people together. Successful management in the digital age requires two skills: championing data science and business analytics in combination with management with a global perspective. This is precisely the combination offered by our BA in Data Science and Business. The program brings together human and artificial intelligence while using progressive teaching concepts to ensure a successful learning journey for all students, regardless of background.

Program facts

• Duration: 3 years / 6 semesters
• Points: 180 ECTS
• Language: English
• Degree: Bachelor of Arts (B.A.)
• Location: Berlin-Mitte
• Start: October

Progressive teaching concept for professional training

The learning environment fostered at Berlin International is student-centered, hands-on, and has a strong focus on an applied, practitioner approach. Our teaching concept focuses on project-based learning and uses a number of innovative teaching techniques, such as case-based teaching, analytical labs and real-life simulations. Students work individually and in groups in order to promote professional and personal growth and the development of team skills. All Bachelor and Master programs at Berlin International are taught in English. In combination with our diverse student and teaching body and our global network, this enables us to offer a truly international academic experience.

Solid training with the accredited BA Data Science & Business program

The BA Data Science & Business at Berlin International has been accredited and evaluated as a quality program with transparent structures, regulations, and qualification targets. Our program thus has proven to conform to the highest quality standards set by the European Higher Education Act. It is accredited by The German Accreditation Council.

Study Data Science & Business at Berlin International

All our Business students acquire the necessary foundations for successful further study during the first year of their program — no prior knowledge is required. The second and third years then focus on students’ chosen specializations.

In the BA Data Science & Business program, students receive a thorough grounding in both management and data science, highlighting the interdependence of these two fields in a data-driven economy. This grounding covers:

• Traditional management courses such as International Business and Strategy, complemented by a set of soft-skills courses such as Team-building and Conflict Management, as well as consulting.
• Courses that sit at the intersection of management and data science, such as Digital Marketing and Platform Business.
• Programming in Python and R, are the two most widely used programming languages in data science. (No prior knowledge of programming is necessary — it is taught in a hands-on manner whereby students get extensive experience with a wide range of datasets, applying machine learning and other analytical techniques.)
• Courses focusing on conceptual modeling techniques and tools, such as Digital Enterprise Management and Database Management.
• Students will have the opportunity to obtain certificates in machine learning and cloud computing from the Amazon Web Services Academy.

These subjects are never abstract but are always taught in an applied manner – the goal is to make the learning journey fun and to kindle intrinsic motivation. Current students value this highly: the courses with the seemingly most difficult material are also those which enjoy the highest rates of student satisfaction!

To gain further hands-on experience and sharpen their expertise, students undertake an internship at an organization of their choice during their fifth semester. Berlin International supports students in preparing for the internship and finding a suitable organization. Finally, the Bachelor Thesis is an opportunity for students to explore a topic that interests them independently and in-depth.

Career opportunities in Data Science & Business

Around the world, there is a severe shortage of skilled professionals who are not only trained in business but also understand and can realize the opportunities that digitization has to offer. Due to this shortage, salaries have risen sharply for anyone working at the intersection of management and data science.

There are many different careers available to students of Data Science & Business upon graduation, both in traditional management roles and in more data-driven, analytic areas of organizations. Given the many different possibilities, the examples below represent only a small sample of such careers:

Business Analyst and Data Scientist

Both business analysts and data scientists use data to understand and quantify business drivers such as what are the core aspects of a product’s success. In addition, data scientists have the skills to develop models that make predictions about, for instance, individual consumers and whether a given consumer is likely to buy again from the company.

Business Developer

A business developer is familiar with the key competencies of the organization and identifies and evaluates opportunities for future growth, such as for a new data-driven product, or the expansion or repositioning of an existing product.

Product Manager

A product manager is responsible for the management of products and serves as a hub connecting the different business units that all work together to ensure a product’s success — units such as sales, development, and legal. A product manager, therefore, needs a broad understanding of all relevant aspects of the business. In a data-driven environment, this entails a deep understanding of the opportunities and limits of machine learning.

Marketing Manager

A marketing manager makes sure that the four Ps — the four essential factors involved in marketing a good or service — are well aligned. These are the product and its positioning in the market with respect to competitors, the price (what the consumer pays), the place (where a product is marketed online or offline), and promotion (i.e. advertising). This role often involves working extensively with data.

Enterprise Architect

Enterprises are complex systems with different organizational units, employees, processes, products and services, customer groups, suppliers, business partners, IT systems, and further resources. By offering a holistic perspective, Enterprise Architects link different views of an organization with conceptual modeling methods. They address the main concerns of key stakeholders and their strategic goals, analyze gaps within the IT landscape, and define the actions to be taken.