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Regular version of the site
Master 2021/2022

Application of Network Theory to Business Analytics and Social Networks

Area of studies: Applied Mathematics and Informatics
When: 1 year, 1-4 module
Mode of studies: offline
Open to: students of one campus
Instructors: Elena Beylina
Master’s programme: Applied Statistics with Network Analysis
Language: English
ECTS credits: 6

Course Syllabus


This course is about key approaches in business analytics and major types of business analytics. Specifically, there will be the focus on necessary vocabulary of business analyst and digital trends in the companies, applied skills in MS Office (Word, Excel, and Power Point). Throughout the semester there will be practical cases in different business fields: organizational studies, communication studies, e-commerce and B2B, consumer marketing insights and others.
Learning Objectives

Learning Objectives

  • The course gives students an important foundation to develop and conduct their own research as well as to evaluate research of others.
Expected Learning Outcomes

Expected Learning Outcomes

  • be able to criticize constructively and think out of the box
  • be able to structure information
  • be able to think logically and consistently
  • be able to understand the basic concepts and business analytics instruments
  • have oral presentation skills
  • have skills of writing business reports and provide analytical reviews
  • to know the area of business analytics and its practical cases
  • to know the fundamentals of working in MS Office (Word, Excel, and Power Point) and Power BI
  • to know topics, terminology, and principles of business analytics
Course Contents

Course Contents

  • Introduction to Business Analytics
  • Digital trends
  • People and Organization
  • Organizational network analysis (case study)
  • Foundation of Innovation Management
  • Blockchain data (case study)
  • Types of business analytics and MS Office
  • Data analytics in communication studies (case study)
  • Introduction to MS Excel
  • Data management in MS Excel
  • e-commerce, B2B
  • Introduction to Power BI
  • Data analysis with VBA
  • Consumer Marketing Insights (case study)
  • Introduction into data visualization
  • Making presentations
Assessment Elements

Assessment Elements

  • non-blocking Project in MS Word
  • non-blocking Project in MS Excel
  • non-blocking Project in Power BI
  • non-blocking Project in MS Power Point
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
  • 2021/2022 2nd module
  • 2021/2022 3rd module
  • 2021/2022 4th module
    0.2 * Project in MS Excel + 0.3 * Project in MS Power Point + 0.1 * Project in MS Word + 0.4 * Project in Power BI


Recommended Core Bibliography

  • Hsinchun Chen, Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503
  • Trott, P. (2016). Innovation Management and New Product Development. Pearson.

Recommended Additional Bibliography

  • Duarte, N. (2008). Slide:ology : The Art and Science of Creating Great Presentations (Vol. 1st ed). Beijing: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=412140
  • Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G. (2018). Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies. Information Systems & E-Business Management, 16(3), 479–491. https://doi.org/10.1007/s10257-018-0377-z