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Высшая школа экономики
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Course Syllabus

Магистратура 2023/2024

Анализ данных для бизнес-исследований

Лучший по критерию «Полезность курса для Вашей будущей карьеры»
Лучший по критерию «Полезность курса для расширения кругозора и разностороннего развития»
Лучший по критерию «Новизна полученных знаний»
Статус: Курс обязательный (Международный бизнес в странах Азиатско-Тихоокеанского региона)
Направление: 38.04.02. Менеджмент
Кто читает: Департамент финансов
Где читается: Санкт-Петербургская школа экономики и менеджмента
Когда читается: 2-й курс, 1, 2 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для всех кампусов НИУ ВШЭ
Преподаватели: Макарова Ольга Всеволодовна
Прогр. обучения: Международный бизнес
Язык: английский
Кредиты: 6
Контактные часы: 48

Course Syllabus

Full Syllabus

Abstract

The course covers aspects of business-planning in an enterprise and performance management in financial perspective. Starting with foundamental strategic and architecrural concepts and questions on linking strategy with operations, students then deep dive into profitability and cost analysis accompanied with revenue planning, will study business modelling, planning and budgeting instruments that support decision-making process in an organization. Students will work with financial models and will analyse in practice strategy-operations linkage and operational financial performance management
Learning Objectives

Learning Objectives

  • This course equips students with basic analytical! frameworks and tools for strategic and operational decision-making in managing enterprise based on financial 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
  • Able to choose calculative methods appropriate to the type of decision-making aspect and substantive research problem
  • Able to conduct quantitative evaluation in decision-making, apply basic accounting and forecasting methods and interpret results of analysis
  • Application of basic tools (plots, graphs, tables) to carry out exploratory data analysis.
  • Construct a financial model for planning and decision-making
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 * Hometask + 0.15 * Project + 0.2 * in-class activity + 0.2 * in-class activity
Bibliography

Bibliography

Recommended Core Bibliography

  • Aguinis, H. (2014). Performance Management: Pearson New International Edition (Vol. 3rd ed). [N.p.]: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1418135
  • Boris Mirkin. (2011). Core Concepts in Data Analysis: Summarization, Correlation and Visualization (Vol. 2011). Springer.
  • Cardy, R. L., & Leonard, B. (2011). Performance Management: Concepts, Skills and Exercises : Concepts, Skills and Exercises (Vol. 2nd ed). Armonk, N.Y.: Routledge. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=929342
  • Enterprise architecture at work : modelling, communication and analysis, Lankhorst, M., 2013
  • Nicola Terracciano. (2017). Performance Management at the Organizational Level. Annals of Spiru Haret University Economic Series, 2, 19.
  • Rohatgi, V. K., & Saleh, A. K. M. E. (2015). An Introduction to Probability and Statistics (Vol. 3rd edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1050364
  • S. Christian Albright, & Wayne L. Winston. (2019). Business Analytics: Data Analysis & Decision Making, Edition 7. Cengage Learning.

Recommended Additional 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.
  • 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.
  • Mohanty, M., & Shankar, R. (2019). A hierarchical analytical model for performance management of integrated logistics. Journal of Management Analytics, 6(2), 173–208. https://doi.org/10.1080/23270012.2019.1608326
  • Pernille Christensen. (2011). An Introduction to Statistical Methods and Data Analysis (6th ed., international ed.). Journal of Property Investment & Finance, (2), 227. https://doi.org/10.1108/jpif.2011.29.2.227.1?utm_campaign=RePEc&WT.mc_id=RePEc
  • Rasch, D., Verdooren, L. R., & Pilz, J. (2019). Applied Statistics : Theory and Problem Solutions with R. Hoboken, NJ: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2218318
  • Strategic enterprise architecture management : challenges, best practices, and future developments, , 2012
  • Zelterman, D. (2015). Applied Multivariate Statistics with R. Springer.

Authors

  • VOLGUTOVA ANASTASIYA ANDREEVNA
  • MAKAROVA OLGA VSEVOLODOVNA
  • SOLOVEVA EKATERINA EVGENEVNA