Course outline

When? - 4 courses à 2h each

How? – Online sessions via MS Teams & homework assignments

We identified that knowledge in analytics and skill levels in MS Excel vary strongly, therefore the sessions start out with more general and simple content, building up towards larger tasks and complex databases. The students have access to a document, explaining the most important functionalities of MS Excel and a separate task file for each session. Between sessions, students are asked to prepare a data analysis task at home which requires approximately 15-30 minutes effort.

The sessions are held online via the streaming service Microsoft Teams and are divided into lecture style as well as hands-on style parts. The students are able to raise individual questions and join one-on-one style break out rooms for personal assistance.

Content and assignments

- Understanding basic descriptive statistics

o Data distributions and normal distribution

o Mean, Median, Mode

o Ranges (Quartiles, Max, Min, Outliers and extreme values)

- Preparing datasets for analysis

o Cleaning data for missing / flawed entries

o Applying correct formatting

o Approaching and structuring large datasets strategically

- Working with MS Excel

o Understanding and applying formulas

o Analysing data with pivot tables

o Creating appealing and understandable visualisations

- Applying knowledge to larger data analysis

o Pricing of goods

o ABC customer analysis

o Interactive dashboard for supplier analysis

Purpose of the workshop

- Develop a structured and analytical approach to solving quantitative problems

- Learn to handle large data sets, especially in regard to cleaning, structuring and preparing data for analysis

- Understand basics of descriptive statistics and data distributions, to question results and improve analysis

- Discuss various visualization methods

- Learn hands-on functions and tools used in MS Excel to speed up analytical processes

Full attendance of all four sessions is mandatory.

Skill seminars help CEMS studens to improve their practical skills under supervision of lecturer from corporate sphere.

- 30% active participation during the workshop

- 30% input and contribution

- 40% collaboration in group works