• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Data Analysis for Business Research

2023/2024
Academic Year
ENG
Instruction in English
6
ECTS credits
Course type:
Compulsory course
When:
2 year, 1, 2 module

Instructor

Course Syllabus

Abstract

The course aims at developing analytical skills for business research. During the course students will learn how to construct analytical system around the business that links strategy with perations. The application of modern business data analytical methods and tools to improve organizational performance will be studied iin practice. The students will learn about different types of data models, their relevance to particular business decisions and organising analytical system for managing divisional and segmental performance The course relies on data study, quantitative analysis and financial modelling which supports construction of explanatory and predictive models in the context of problem solving and organizational decision-making. Students will research and perform a real-case project how real business applies analytical tools in practice and construct and analyse analytical and financial models for business research.
Learning Objectives

Learning Objectives

  • This course equips students with basic analyticall frameworks and tools for strategic and operational decision-making in managing enterprise based on data analysis and data modelling
Expected Learning Outcomes

Expected Learning Outcomes

  • Able to choose statistical methods appropriate to their data and substantive research problem
  • Able to conduct descriptive statistics on quantitative data, apply basic statistical methods and interpret results of analysis
  • Application of basic tools (plots, graphs, summary statistics) to carry out exploratory data analysis.
  • Ability to analyse and decompose organization structural elements to create an analytical model for performance management
Course Contents

Course Contents

  • Introduction to Business Analysis
  • Constructing the enterprise analytical system
  • Financial Structure of Organization
  • Introduction to data analysis
  • 5. Management Control Systems and Budgeting
  • Analytical models and tools of perfromance and management
  • Using data for decision-making
  • Project budgeting
Assessment Elements

Assessment Elements

  • non-blocking in-class activity
    attendance and activity at lessons, in-class tasks & hometasks completion and presentations, initiating contentive knowledge-based discussions
  • non-blocking Project
    Group project, field research on practical implementation of business analysis tools, interviewing business practitioners.
  • non-blocking Hometask
    Hometask on using data and financial modelling for decision-making
  • non-blocking Exam
    Exam in written form, consists of multiple choice questions, calculative tasks and open questions tasks.
Interim Assessment

Interim Assessment

  • 2023/2024 2nd module
    0.3 * Exam + 0.15 * Project + 0.2 * in-class activity + 0.15 * Hometask
Bibliography

Bibliography

Recommended Core Bibliography

  • Fraser C. Business statistics for competitive advantage with Excel 2016: basics, model building, simulation and cases. New York, NY: Springer Science+Business Media, 2016. 475 с.
  • Boris Mirkin. (2011). Core Concepts in Data Analysis: Summarization, Correlation and Visualization (Vol. 2011). Springer.
  • Enterprise architecture at work : modelling, communication and analysis, Lankhorst, M., 2013
  • S. Christian Albright, & Wayne L. Winston. (2019). Business Analytics: Data Analysis & Decision Making, Edition 7. Cengage Learning.

Recommended Additional Bibliography

  • Business Analysis & Valuation: IFRS Edition. (2007). Thomson Learning. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsnar&AN=edsnar.oai.cris.maastrichtuniversity.nl.publications.9a0d36f2.def1.42ca.8628.dc936372947e
  • Clark, D. (2017). Beginning Power BI : A Practical Guide to Self-Service Data Analytics with Excel 2016 and Power BI Desktop (Vol. Second edition). Camp Hill, Pennsylvania: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1478775
  • Cokins, G. (2009). Performance Management : Integrating Strategy Execution, Methodologies, Risk, and Analytics. Hoboken, N.J.: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=317048
  • Danielle Stein Fairhurst (2015). Using Excel for Business Analysis
  • Enterprise architecture as strategy : creating a foundation for business execution, Ross, J. W., 2006
  • Groebner, David, et al. Business Statistics, EBook, Global Edition, Pearson Education, Limited, 2018. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=5186156.
  • Nicola Terracciano. (2017). Performance Management at the Organizational Level. Annals of Spiru Haret University Economic Series, 2, 19.
  • Strategic enterprise architecture management : challenges, best practices, and future developments, , 2012