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Regular version of the site

Research Seminar "Application of Network Theory to Business Analytics and Social Networks"

2023/2024
Academic Year
ENG
Instruction in English
6
ECTS credits
Course type:
Elective course
When:
1 year, 1-4 module

Instructor

Course Syllabus

Abstract

This course is about different 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 and applied skills in MS Office (Word, Excel, and Power Point). Throughout the semester there will be practical cases in different business fields as well as discussion of practice-oriented term papers. The seminar is aimed at developing students' skills of research work and applications of theoretical knowledge to solving practical cases.
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

  • By the end of the course the students are expected to be able to undertake a substantial research project through which to demonstrate their research and analytical skills and how well they can apply a given theoretical understanding and methodology to a set problem.
  • - - be able to design and understand the structure of data; use various visual and table presentations of data.
  • Be able to present and/or interpret data in tables and charts.
  • - Use storytelling when giving a presentation.
  • A student compares research design
  • A student can choose proper tools and instruments for data visualization
  • A student can prepare his data for visualization
  • Are able to describe and justify chosen research design and methodology
  • Be able to escribe graph/diagram, analysing visual prompts, interpret tables/charts.
  • Acquiring capability to analyze and comment scientific results from a specific research topic
  • an ability to solve analytical and research problems with modern technical means and information technologies; an ability to organize their activities in the framework of professional tasks.
  • Distinguish between qualitative and quantitative research methods;
  • Apply the basics of social network analysis at the network level (e.g. density, clustering, degree distribution, etc.); at the node level (e.g. degree, betweenness, closeness); at the subgraph level (e.g. triads, communities)
  • Able to build integrated reports and dashboards
  • Ability to formulate research question, and explain how the question and theory define methodology;
  • - to learn the fundamental analytical scheme starting from data preparation and ending up with data visualisation in a form of a dashboard in Power BI
  • - develop critical assessment and academic presentation skills;
  • - to develop their presentation skills and abilities to participate in the discussions
  • Able to demonstrate knowledge on the principles for data visualization
  • Be able to present a model using a dashboard, charts, etc.
  • Be able to build model for measuring efficiency - Data Envelopment Analysis model - in R
  • Be aware of Open Data sources
  • Be able to extract the data using API
  • Be able to apply text mining in your own tasks
  • Be able to draw basic processes using BPMN 2.0 notations
Course Contents

Course Contents

  • 1. Introduction to Business Analytics
  • 2. Introduction to Research Projects
  • 3. Performance Evaluation
  • 4. Social Network Analysis: Applications for Organizations
  • 5. Analytical Process: from Business Problem to Solution
  • 6. Customer Analytics
  • 7. Contemporary Text Analysis
  • 8. Business Process Management and Financial Modelling
  • 9. Research Methodology
  • 10. Office skills: text and data formatting
  • 11. Visual Communications: Charts
  • 12. Dashboards and Visual Analytics
  • 13. Data Analysis and Visualisation with Power BI
  • 14. Network Visualisation for Better Decision-Making
  • 15. Making Presentations
  • 16. Research Paper
Assessment Elements

Assessment Elements

  • non-blocking Test
  • Partially blocks (final) grade/grade calculation Homework
  • Partially blocks (final) grade/grade calculation Project
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.1 * Homework + 0.15 * Homework + 0.15 * Homework + 0.3 * Homework + 0.1 * Project + 0.05 * Test + 0.05 * Test + 0.05 * Test + 0.05 * Test
Bibliography

Bibliography

Recommended Core Bibliography

  • A practitioner's guide to business analytics : using data analysis tools to improve your organization's decision making and strategy, Bartlett, R., 2013
  • Business analytics : data analysis and decision making, Albright, S. C., 2020
  • Business research methods, Bell, E., 2019
  • English for academic study: Extended writing & research skills. Course book, McCormack, J., 2012
  • Exploratory social network analysis with Pajek, Nooy de, W., 2018
  • Grant, R. (2019). Data Visualization : Charts, Maps, and Interactive Graphics. Boca Raton, Florida: Chapman and Hall/CRC. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1944722
  • Models and methods in social network analysis, , 2006
  • Seamark, P. (2018). Beginning DAX with Power BI : The SQL Pro’s Guide to Better Business Intelligence. [United States]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1743806
  • Social network analysis : methods and applications, Wasserman, S., 2009
  • Writing a Research Proposal in English, учебное пособие по академическому письму на английском языке для студентов экономических специальностей, НИУ Высшая школа экономики - Нижний Новгород, 189 с., Меркулова, Э. Н., Ненашева, Т. А., 2014
  • Кузин А.В., Чумакова Е.В. - Основы работы в Microsoft Office 2013 - Издательство ФОРУМ - 2022 - ISBN: 978-5-00091-024-5 - Текст электронный // ЭБС ZNANIUM - URL: https://znanium.com/catalog/document?id=400038
  • Платова, Е. Д. Effective Presentations in English : учебное пособие / Е. Д. Платова. — Оренбург : ОГУ, 2019. — 140 с. — ISBN 978-5-7410-2406-5. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/160030 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.
  • Феррари, А. Анализ данных при помощи Microsoft Power BI и Power Pivot для Excel : руководство / А. Феррари, М. .. Руссо , перевод с английского А. Ю. Гинько. — Москва : ДМК Пресс, 2020. — 288 с. — ISBN 978-5-97060-858-6. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/179497 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Recommended Additional Bibliography

  • 100 questions (and answers) about survey research, Ruel, E., 2018
  • Empirical political analysis : quantitative and qualitative research methods, Brians, C. L., 2011
  • Marketing research : an applied orientation, Malhotra, N. K., 2020
  • Real world research : a resource for users of social research methods in applied settings, Robson, C., 2016