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Книга
Маркетинг новых продуктов

Артемьева М. В., Фоменков Д. А.

Н. Новгород: Нижегородский государственный технический университет им. Р.Е. Алексеева, 2022.

Глава в книге
Design of Intelligent Enterprise Systems Focused on Economic Efficiency

Garina E. P., Garin A. P., Kuznetsov V. P. et al.

In bk.: Business 4.0 as a Subject of the Digital Economy. Springer, 2022. P. 737-740.

Препринт
Representation of Family Policy in Russian Printed Media with Different Political Orientation: Pro-Natalist Turn of 2006

Kim N.

Social Science Research Network. Social Science Research Network. SSRN, 2016

Data-driven Culture

2024/2025
Учебный год
ENG
Обучение ведется на английском языке
6
Кредиты
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
Когда читается:
1-й курс, 3, 4 модуль

Преподаватели

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
  • non-blocking Homework 3
  • non-blocking Homework 4
Interim Assessment

Interim Assessment

  • 2024/2025 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

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