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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: 2026-02-05 16:02:17

Abstract

This lecture covers organizations and businesses' end-to-end data analytics process and deepens each process stage. It shows why a stage is needed and what actions are taken in each stage. It gives steps successfully applied in practice and loopholes when issues arise. Case studies from various industries will be presented for each stage.

Objective

This course aims to give the students an understanding of the whole data analytics life cycle in the business world. It shows the expectations of companies and how it is measured. It enables the student to manage successfully all the non-methodological aspects of a data analytics project which are the primary source of failure in end-to-end executions. The student will become familiar with the "business language, and cultural aspects of organizations. It also gives an overview of the data analytics tool, platform, and methods ecosystem for successfully technical data analyses.

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

  • Statistics Master (The following courses belong to the curriculum of the Master's Programme in Statistics. The corresponding credits do not count as external credits even for course units where an enrolment at ETH Zurich is not possible.)
  • Quantitative Finance Master (see Students in the Joint Degree Master's Programme "Quantitative Finance" must book University of Zurich modules directly at the University of Zurich. Those modules are not listed here.)