Business Analytics

The proposed three-year study programme, Business Analytics, aims to prepare experts in business data analytics and data-driven approaches to the decision-making processes.

The study of the programme is focused on solving challenges that companies and organisations face in the time of big data, and that cannot be solved without the help of professionals who are focused both on business and management and in statistical modelling and information technology. Therefore, this study programme differs in terms of its focus on business and management from other study programmes in the area of data science offered by other IT faculties.

The educational objectives place emphasis on understanding the issue’s context from the perspective of companies and organisations, as well as the adoption of the concepts of data analysts. The study is practically oriented and is suitable for applicants who are interested in the connection between business management and data sciences.

After successfully completing his/her studies the graduate is able to:

• identify those business issues and tasks that can be effectively solved with data analytics tools.
• understand the results and interpret the results of data analytics at a business level.
• work at a user level with database systems.
• visualise and report data and analysis in accordance with the assigned tasks and problems.
• control the user-level basic technology tools for data analysis and statistical modelling.
• understand the principles of statistical methods and the methods of operations research, know their capabilities in the fields of business and entrepreneurship and apply them in these areas.
• based on the acquired knowledge and skills, develop and properly report data analysis for a particular business assignment.
• understand the business context environment

Graduates of this programme can offer their future employers the combination of interdisciplinary knowledge and skills connecting data analytics with business areas. This combination enables a broad application wherever there is the need for working creatively with data and technologies to present a competitive advantage in business. And enhances graduates‘ employability in a wide range of industries at the positions of analysts, consultants and various managerial jobs.

Part of the study is the mandatory practical training experience of at least 12 weeks, which can be divided during the study into multiple blocks, so that, in the summary, the student has earned 16 credits. Students can have practical experience in various enterprises and organisations of their choice, if they are approved by the guarantor of the practical course, or choose from multiple options of pre-agreed experience placements. Practical training will follow either the CRISP-DM methodology where appropriate or similar one to ensure the practical relevance for real-life business problems and their solutions.

Elaboration of the final work of about 30-35 pages (without attachments) should verify the ability of students to apply a problem-oriented approach to interest entities (businesses, public and state institutions, non-profit organizations, cities and regions, information systems, etc.), search for a necessary set of relevant information, identify and accurately describe problem fields in accordance with acquired theoretical knowledge, determine appropriate methods and procedures for their analysis, describe and analyze obtained data and propose specific and typically realistic solutions to the formulated problem. The focus of the final work and its practical outcomes will be closely linked to the compulsory course of Practice, both content and form will be decided on in cooperation with the supervisor.

A graduate of the Bachelor degree of Business Analytics can (after meeting the criteria of acceptance) continue in any follow-up Master’s study. At the Faculty of Economics and Administration (after meeting the requirements of acceptance), it’s especially possible to continue in the follow-up Master’s programme, Business Informatics.