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Business Big Data Analytics

The study programme is focused on business big data, synergy in development of mathematical and computer science skills and competencies, development of mathematical models for business development decisions. Graduates are able to analyse the business big data, to identify business problems, optimize business processes, apply acquired knowledge and to create mathematical models and algorithms for business decisions and business insights development.


Description of Study Programme
Location Faculty of Mathematics and Natural Sciences
Cycle Second cycle
Field Applied Mathematics, Informatics, Economics
Language Lithuanian
Form Full-time studies - 2 y. (weekend, evening-time; cyclic, blended learning), Part-time studies - 3 y. (weekend, evening-time; cyclic, blended learning)
Degree awarded Master of Mathematical Sciences
Yearly Price  i Full-time studies - 4787 €
Part-time studies - 3191 €

Entry requirements

Minimum requirements


Score structure

Component Coefficient
First component of the competition score

Average grade (CGPA) of University‘s Bachelor’s degree (min. length – 180 ECTS) and its supplement


Second component of the competition score

Research activities


Third component of the competition score

Motivation letter and online interview



Tuition fee

The tuition fee applied for the academic year 2021-2022 is indicated below.

Foreign nationals with Lithuanian origins and EU citizens
Full-time studies 4787 €
Part-time studies 3191 €
Price per credit 79,78 €
Partial tuition fee waiver can be applied for the study price.


Financial support






Subjects of the study programme by semesters


Analysis of Business Big Data and Decision Making Analysis of business processes and identification of problems Design of business systems, risk evaluation, prediction and optimisation Development of business big data analytic tools and design of software




Why @KTU?

Strong links with industry partners

KTU launched the first in Lithuania study programme for business big data analysis with strong engagement of industry partners to facilitate growing demand for the specialists in the field.

Why @KTU?

Cooperation with international experts

Practical seminars are conducted by Lithuanian and international experts from leading business companies (Western Union, Adform, Barclays, Execaster, etc.).

Why @KTU?

Latest software tools

Case-based teaching and problem-based learning facilitates understanding of ongoing challenges and application of real-life solutions using Spark, Python, Scala, SAS, R software.



Student’s competences

– Big data analytics and decision making
– Analysis of operational processes of business organisations and identification of problems
– Modelling of business systems, risk assessment, forecasting and optimisation
– Development of algorithms and software for big data analytics

Student’s skills

– Able to integrate and apply acquired knowledge of mathematics, informatics and business, develop models for analytics of big data sets
– Able to find, select and understand scientific literature and use knowledge of scientific research in solving of the tasks of big data analytics
– Able to systemically substantiate, plan, organise and perform research of big data sets, knows mathematical methods suitable for creation of models for big data analysis, understands the stages of analysis and methodology of their performance, and is able to apply it
– Able to understand performance processes of business organisations, efficiency indicators, factors which determine decision-making, is able to use them for creation of mathematical models
– Able to create mathematical models for analytics of big data sets, select parameters, verify a model’s suitability or available data, to compare several models
– Able to create and use metadata, specify consumer’s needs and restriction for the information system
– Able to initiate, prepare, implement and present projects, interpret the received results of business systems, prepare analysis reports, formulate reasoned conclusions and forecasts, convey knowledge and understanding to the managers involved in decision-making of business, take responsibility for results and quality of his/her work



You may become

 – Development and maintenance of the big data repository
 – Development, installation and maintenance of business analytics systems
 – Development and maintenance of report system
 – Data processing, structuring and graphic display
 – Provision of business analysis and summarised insights to the managers
 – Analysis of data and business processes
 – Improvement and maintenance of business analytics system
 – Data processing, structuring and graphic display
 – Preparation of customer assessment reports
 – Preparation of process documentation, process modelling, assessment of performance, financial and economic indicators

 – Effective and high quality planning of the division’s activities, organisation and control of the work of subordinate employees, decision-making on the issues of organisation of the division’s work and personnel management
 – Management and optimisation of the division’s budget
 – Analysis of relevant data, provision of insights and proposals
 – Provision of proposals regarding implementation of effective and innovative solutions
 – Collection, structuring and analysis of financial and other data related to the company’s activities
 – Preparation of reports and provision of information to the management and structural divisions
 – Participation in preparation of the budget, forecasts of monetary flows while assessing investment projects and preparing operational plans




Karolis Urbonas

Karolis Urbonas

Western Union, Applied Business Intelligence Manager in Europe


Our company has countless amounts of data but it cannot be simply laying in a drawer. We need people to work with it, who will manage to use it in order to extract insights about improving some of the processes, do research and make conclusions about the customers’ behaviour. Our clients make 29 transfers in one second, therefore, we accumulate enormous amounts of data in the whole world every day. The company really needs specialists, who could work with large arrays of data. Very often, candidates with such experience dictate the price for us themselves.