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Data Analytics in Organisations and Business
Last Updated: 2026-02-05 15:47:28
Abstract
On the end-to-end data analytics process in organizations & businesses and how to transform data into insights for fact-based decisions. Presentation of the process from the beginning with framing the business problem to presenting the results and making decisions using data analytics. For each topic, case studies from the financial service, healthcare, and retail sectors will be given.
Objective
This course aims to give the students an understanding of the data analytics process in the business world, with a particular focus on the skills and techniques used besides the technical skills. The student will become familiar with the "business language," current problems, and thinking in organizations and business and tools used.
Content
Framing the Business Problem Framing the Analytics Problem Data Methodology Model Building Deployment Model Lifecycle Soft Skills for the Statistical/Mathematical Professional
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 |
|
2 h weekly |
| exercise | Data Analytics in Organisations and Business |
|
1 h weekly |
Offered In
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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.)
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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.)
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Economic Theory for Finance (For possible additional course offerings see )
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