MPM_BADM Business Analytics - Data Analysis and Decision Making

Faculty of Economics and Administration
Spring 2019
Extent and Intensity
2/0/0. 8 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Vojtěch Přibyla, MBA (lecturer)
Guaranteed by
doc. Mgr. Maria Králová, Ph.D.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Supplier department: Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Timetable of Seminar Groups
MPM_BADM/01: Thu 16:00–17:50 VT206, V. Přibyla
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
Course objectives
At the end of the course students should be able to demonstrate: • Competence in data analysis with suitable MS Excel tools • Competence to build up complex models in MS Excel for data analysis • Competence of correct results interpretation in business context • Understanding of basic statistical principles and ability to apply it on real cases • Understanding of relying business theory and ability to actively use knowledge the theory for necessary decisions
Syllabus
  • Introduction into business analytics • Fundaments of data analysis and decision making • Data analysis and decision making in Finance • Data analysis and decision making in Human Resources • Data analysis and decision making in Customer Relationship • Risk management and data analysis • Planning and budgeting • Basics of Enterprise Resource Planning
Literature
    recommended literature
  • DYCHÉ, Jill. The CRM handbook: A business Guide to Customer Relationship Management. Fifteenth printing. Indiana, US: Addison-Wesley, 2012. ISBN 978-0-201-73062-3. info
    not specified
  • ALBRIGHT, S. Christian and L. Wayne WINSTON. Business Analytics: Data Analysis & Decision Making. 5th Edition. Stamford, US: CENGAGE Learning, 2015. ISBN 978-1-133-62960-3. info
  • BREALEY, A. Richard, C. Stewart MYERS and Franklin ALLEN. Principles of Corporate Finance. Eleven edition. Berkshire, UK: McGraw-Hill Education, 2014. ISBN 978-0-07-715156-0. info
Teaching methods
The course is based on three fundamental principles: Business-Related Approach Proper balance between theory and practical cases aims to develop deep understanding of data analysis and the usage in practice. In addition, students will have a chance to train their brains on complex issues and build up their own practical data analytical toolkit. Individual Work Individual exercises on real cases and theory study will develop own capabilities for each student in adequate pace without irrational pressure. Group Knowledge Sharing Chance to share and debate in group a student own solutions will develop their knowledge and improve group communication skills.
Assessment methods
Final grade will be determined as follows: • Final exam: 50% (30 % written, 20 % oral) • In class Participation: 10% • Case studies: 40% You are expected to come to class prepared and ready to discuss and participate during lessons.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2017, Autumn 2017, Spring 2018, Spring 2020, Spring 2021, Spring 2022, Spring 2023.
  • Enrolment Statistics (Spring 2019, recent)
  • Permalink: https://is.muni.cz/course/econ/spring2019/MPM_BADM