• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
For visually-impairedUser profile (HSE staff only)SearchMenu
Master 2020/2021

Application of Network Theory to Business Analytics and Social Networks

Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Area of studies: Applied Mathematics and Informatics
When: 1 year, 1-4 module
Mode of studies: offline
Instructors: Elena Beylina
Master’s programme: Applied Statistics with Network Analysis
Language: English
ECTS credits: 6

Course Syllabus

Abstract

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

  • to know topics, terminology, and principles of business analytics
  • 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
  • be able to criticize constructively and think out of the box
  • be able to understand the basic concepts and business analytics instruments
  • be able to structure information
  • be able to think logically and consistently
  • have skills of writing business reports and provide analytical reviews
  • have oral presentation skills
Course Contents

Course Contents

  • Introduction to Business Analytics
    The session covers the foundations of Business Analytics, provides the description of marketing technological landscape and general business analytical framework.
  • Digital trends
    The session will look at the key concepts in digital organization and digital transformation in the company: how the technology changes business and what are the digital trends. Digital strategy will be discussed in terms of digital transformation of the company.
  • People and Organization
    The session will cover different organizational structures used for data analytics and new product development teams. Several ways of working in a team will be discussed (in particular, agile ap-proach). Key requirements and necessary skills for business analyst will be described (as well as soft skills such as teamwork, stress resistance, argumentation skills, etc.)
  • Organizational network analysis (case study)
    This practical session will be devoted to practical methods of analyzing the organization (with social network analysis): approaches, methods, and applications.
  • Foundation of Innovation Management
    The session will cover the key topics in Innovation Management: what is innovation, sources of innovation, managing innovation. Additional focus will be done on
  • Blockchain data (case study)
    This practical session will be devoted to practical methods of using data in blockchain: vocabu-lary, approaches, methods, and applications.
  • Types of business analytics and MS Office
    The session will summarize the key approaches to business analytics and provides the details of different types of it. Additionally, MS Office tips and tricks will be discussed as well as academic and business requirements to the documents.
  • Data analytics in communication studies (case study)
    This practical session will be devoted to real-life practical case in communication studies field: data extraction, data cleaning, data analytics, major approaches, methods, and applications.
  • Introduction to MS Excel
    The session will look at the basics of the program MS Excel: what it is used for, common notions and fundamental functions. Special focus will be placed on Pivot Table.
  • Data management in MS Excel
    The session will be about working with data in the software: formatting, data validation and con-solidation with such tools as Power Pivot & Power Query.
  • e-commerce, B2B
    This practical session will be devoted to basics of e-commerce, B2B marketing analytics, web and digital in FMCG sector: key terms, approaches, methods, and applications.
  • Introduction to Power BI
    During this session students will learn about key principles of Power BI with additional knowledge of database theory.
  • Data analysis with VBA
    This session will look at VBA as additional tool for data analysis and automatization.
  • Consumer Marketing Insights (case study)
    This practical session will cover the inputs for consumer marketing insights department specialists: key requirements, approaches, methods, and applications.
  • Introduction into data visualization
    This session will cover the rules and tips & tricks for making visualizations, different open sources will be used. Different types of data visualizations will be covered.
  • Making presentations
    This session broadly explains the presentations and visualizations rules and techniques: starting from data visualization history and ending with specific skills for presentations creations (Power Point and other available tools). All the necessary information for business and consulting presentations will be given.
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

  • Interim assessment (4 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
Bibliography

Bibliography

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