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Regular version of the site
2023/2024

Data-driven Culture

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'
Type: Mago-Lego
Delivered by: Department of Marketing (Nizhny Novgorod)
When: 3, 4 module
Open to: students of one campus
Language: English
ECTS credits: 6
Contact hours: 40

Course Syllabus

Abstract

The course helps students to learn how to set analytic goals, work with data in a team, select data analysis methods, and make decisions based on data. If students know basic statistics and use Python, R, or SPSS for analysis, it helps students to better understand the course topics.
Learning Objectives

Learning Objectives

  • Know job requirements. Set and decompose analytic goals and metrics
  • To learn how to set analytic goals, work with data in a team, select data analysis methods, and make decisions based on data.
Expected Learning Outcomes

Expected Learning Outcomes

  • Know job requirements. Set and decompose analytic goals and metrics
  • Select and apply data collection, preparation and analysis methods and tools.
  • Prepare a report and explain (present) results.
Course Contents

Course Contents

  • Marketing analytics jobs and goals
  • Data collection, preparation and analysis
  • Report and presentation of results
Assessment Elements

Assessment Elements

  • non-blocking Homework 1
    Homework on end-to-end analytics or/and cohort analysis
  • non-blocking Homework 2
    Homework on modeling
  • non-blocking Homework 3
    Homework on pivot tables
  • non-blocking Homework 4
    Homework on vizualization
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.25 * Homework 1 + 0.25 * Homework 2 + 0.25 * Homework 3 + 0.25 * Homework 4
Bibliography

Bibliography

Recommended Core Bibliography

  • Phillips, Tim. Data-Driven Business: Use Real-Life Numbers to Improve Your Business by 352% [Электронный ресурс] / Tim Phillips; БД books24х7. – Infinite Ideas, 2016. – 160 pages. – ISBN 978-1908984609. –Режим доступа: http://common.books24x7.com/toc.aspx?bookid=130361. – Загл. с экрана.

Recommended Additional Bibliography

  • Foreman, John W. Data Smart: Using Data Science to Transform Information into Insight [Электронный ресурс] / John W. Foreman; БД books24х7. – John Wiley & Sons, 2014. – 432 pages. – ISBN 978-1-118-03496-5. – Режим доступа: http://common.books24x7.com/toc.aspx?bookid=58144. – Загл. с экрана.Foreman, John W. Data Smart: Using Data Science to Transform Information into Insight [Электронный ресурс] / John W. Foreman; БД books24х7. – John Wiley & Sons, 2014. – 432 pages. – ISBN 978-1-118-03496-5. – Режим доступа: http://common.books24x7.com/toc.aspx?bookid=58144. – Загл. с экрана.
  • Jeffery, M. Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know [Электронный ресурс] / Mark Jeffery; БД ebrary. – John Wiley & Sons, Incorporated, 2010. – 323 p. – ISBN 9780470504543. – Режим доступа: https://ebookcentral.proquest.com/lib/hselibrary-ebooks/reader.action?docID=485632&query=Data-Driven+Marketing. – Загл. с экрана.

Authors

  • Попова Екатерина Петровна
  • LYUBCHANSKAYA ELENA ALEKSANDROVNA
  • Aleksandrovskii Sergei VLADIMIROVICH