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401-4633-00L 5 Credits MSC D-MATH
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Data Analytics in Organisations and Business

Lecturers & Examiners: Dr. Isabelle Flückiger
VVZ CR n/a

Last Updated: 2026-06-01 11:31:28

Abstract

This lecture explores the end-to-end data analytics process for organizations and businesses, guiding through each stage. It explains the necessity of each stage, outlines the actions undertaken, and highlights proven steps successfully applied in practice. It examines potential pitfalls and how to address them. Case studies from various industries will be presented to illustrate each stage.

Objective

This course aims to provide students with a comprehensive understanding of the entire data analytics life cycle within the business world. It highlights the expectations of companies and the metrics used to measure them. The course equips students to successfully manage non-methodological aspects of data analytics projects, which are often the primary sources of failure in end-to-end executions. Additionally, students will become familiar with the 'business language' and the cultural nuances of organizations. The course also offers an overview of the ecosystem of tools, platforms, and methods essential for performing technical data analyses effectively.

Content

1) Introduction 2) Framing the business problem 3) Framing the analytics problem 4) Data 5) Identification of problem-solving approaches and appropriate tools 6) How to set up and validate models 7) The deployment of a model 8) Model lifecycle 9) Operating models and roles 10) Some words about soft skills needed by statistical and mathematical professionals

Resources

Lecture Notes

The lecture's presentation slides will be provided.

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 120 minutes
Aids
Summary 10 A4-pages (i.e. 5 sheets)

Course Components

Type Title Time & Place Hours
lecture Data Analytics in Organisations and Business
  • Fri 14:15-16:00 (HG G 5)
2 h weekly
exercise Data Analytics in Organisations and Business
  • Fri 16:15-18:00 (HG G 5)
1 h weekly

Offered In

  • Statistik Master (Die hier aufgelisteten Lehrveranstaltungen gehören zum Curriculum des Master-Studiengangs Statistik. Die entsprechenden KP gelten nicht als Mobilitäts-KP, auch wenn gewisse Lerneinheiten nicht an der ETH Zürich belegt werden können.)
  • Quantitative Finance Master (siehe Studierende im Joint Degree Master-Studiengang "Quantitative Finance" müssen Module der Universität Zürich direkt an der Universität Zürich buchen. Die entsprechenden Module sind hier nicht aufgelistet.)