Compare
There are no other study programmes for comparison
 | Loading… |
Search study programmes for comparison:
Compare
Business Big Data Analytics
Institutions providing this programme
Programmes with similar name
Programmes granting same qualifications
Summary of the Profile
Objective(s) of a study programme:
To provide comprehensive knowledge of mathematics, informatics, and economics, develop the ability to analyze big business datasets, identify problems of economic entities, apply the acquired knowledge, develop mathematical models and algorithms for decision-making by economic entities, and provide insights.
Description of the study programme: https://admissions.ktu.edu/programme/m-business-big-data-analytics/
Learning outcomes:
Knowledge and its application:
Have ability to think logically and analytically by integrating various areas of data - operational/business, analysis - expert knowledge, setting structural requirements, designing an algorithm and creating computer programs to implement mathematical models.
Have ability at conceptual level to identify economic and business issues, to analyse, to plan and to forecast institutions and business actions in areas that have big data and the need to analyse it.
Have ability to abstract economic activity information, to describe processes of activity systems using mathematical relationships.
Have ability to deal with non-standard complex economic activity tasks in new and unfamiliar environments combining mathematics, computer science and economic and big data knowledge.
Have ability to compare several solutions for the same issue and to find the optimum way according to selected criteria.
Have ability to develop algorithms and computer programs for created models realization, to work with big data.
Have ability to transform heuristic arguments in mathematical proofs; prove the assertions, similar to the known.
Have ability to understand mathematical statements, their proofs and interrelationships and apply them in a variety of contexts.
Research skills:
Have ability to apply mathematical knowledge related to process and event analysis, prognosis, optimization, risk assessment and big data.
Have knowledge of economic policy-making institutions and business organizations’ operational processes, efficiency indicators, modelling principles, factors influencing decision-making, and able to use them for development of mathematical models.
Can explain the importance of big data management in the organization, and able to use databases, to create and use metadata, to specify user needs and limitations of the information system.
Have ability to choose the appropriate mathematical methods for the development of business big data analysis models, understand the analysis phases and their application stages, and apply it in the interdisciplinary area.
Have ability to describe of the modern economic and business analytics systems’ architecture, programming languages and their application possibilities for business big data analysis models realization given the limited computational technological resources.
Have ability to integrate and apply the acquired knowledge of mathematics, computer science and economic activity, to identify the new trends and mathematical methods and have the skills to use them developing the business big data analysis models.
Special abilities:
Have ability to collect, summarize, systematize, analyse, evaluate any information regardless of its form (audio, video, text, tactile, etc.).
Have ability to find, to collect and to perceive a scientific literature in mathematics and to use their knowledge of research in big data analysis tasks.
Have ability methodically to justify, to plan, to organize and to perform analysis of business big data.
Have ability to integrate knowledge of business, informatics and various mathematical modelling methods.
Have ability to create mathematical models for analysis of business big data, to select parameters, to test model relevance for available data, to compare few models with each other.
Have ability to initiate, to organize, to execute and to communicate projects, to interpret the results, and to formulate relevant conclusions and prognosis for investigated business systems.
Have ability to prepare reports and analytical insights, to communicate knowledge and understanding for managers, who make business decisions.
Developed social and personal abilities:
Have ability to critically evaluate their own and others performance and professional experience.
Have ability to make independently decisions, to considering their consequences and their complexity.
Have ability to work independently and in the interdisciplinary team, to generate new ideas; to integrate knowledge and skills.
Have ability to take responsibility for the results and quality.
Have ability clearly and reasonably to present information for colleagues and specialists of other disciplines, have good communication skills.
Have ability to choose the direction of enhancement and to develop acquired skills as needed.
Have ability to recognize, uphold and nurture the most important values of the academic and professional field: justice, honesty, respect for human beings, tolerance, professional, scientific and civic responsibility.
Activities of teaching and learning:
The studies include classroom work (lectures, practical work, laboratory work, seminars, outgoing visits to enterprises, etc.) and individual work for mastering theoretical material, preparation for classroom work, intermediate and final assessments and performing other activities. The studies of each study module are completed by the assessment of the student’s knowledge and skills – an examination or another final assessment; the study programme is completed by the final degree project and its defence.
Methods of assessment of learning achievements:
The applied cumulative assessment system of the learning outcomes ensures constant and involving work of students during the entire semester of studies; the final evaluation of the study module consists of the sum of the grades of intermediate assessments and the final assessment multiplied by the weighting coefficients (percentages of components).
Study subjects (modules):
Big Data Mining Methods, Bigdata Research Project, Matrix Analysis, Strategic Business Analysis, Multivariate Statistical Analysis Models, Optimization and Decision Making, Project of Business External Data Analytics, Business Risk and Uncertainty Analytics, Project of Business Internal Data Analytics, Master’s Degree Final Project.
Electives: Analytics of Finance and Accounting Data, Time Series Analysis, Python for Data Science, Modelling of Marketing Decisions, Information Systems Requirements Analysis and Specification, Financial Markets Models, Financial Management Decisions, Data Analytics and Visualization, Consumer Analytics, Business Environment Forecasting, Big Data Analytic Tools.
Study programme abstract:
A graduate has comprehensive and relevant interdisciplinary knowledge in mathematics, computer science, economics and is able to apply it for the analysis of big data in business. The graduate is able to integrate and apply the acquired skills to gain insights for economic entities by creating and developing business strategies and models aimed to predict the demands and behaviour of competitors, customers and suppliers, optimize sales and channels of distribution, as well as consumption of resources, analyse, measure and predict financial results and risk.
Access to professional activity:
The graduate can work as an analyst in big data and business systems, consultant for solutions, risk assessment and management positions in various business organisations (e-commerce, transportation, logistics, pharmaceutics, health care, finances, insurance, telecommunications) and governmental institutions.
Access to further study:
S/he has access to the third cycle studies.
