Applied Data Research

22B1835

Bachelor

English

5.0

winter- and summerterm

1 semester

The amount of existing and newly generated data in the world is increasing at an unprecedented rate. This growth poses an opportunity for businesses and organisations to derive meaningful insights and trigger the change that creates value and competitive advantage.

Applied Data Research provides a thorough grounding in concepts related to (automated) data collection, screening, processing, analysing, quantifying, visualising and interpreting. The course introduces some of the advanced qualitative and quantitative methods used in research studies. It combines software-aided data analysis with decision-making training, thus providing students with a better understanding of the insights provided by data.

1. Introduction to appropriate software

2. Qualitative research methods

3. Quantitative research methods

4. Automated data collection

5. Presentation of results and storytelling

6. Planning and conducting a small study involving qualitative and quantitative methods

The total workload for the module is 150 hours (see also "ECTS credit points and grading").

• Portfolio exam or
• Portfolio exam or
• Homework / Assignment

PFP 1: Homework (50 %) + written Project report (50 %)

PFP 2: Homework (50 %) + 1h Exam (50 %)

Homework: approx. 10-15 pages

PFP 1

• Homework (written paper): approx. 10 pages
• Written project report: approx. 10 pages

PFP 2

• Homework (written paper): approx. 10 pages
• Written examination: in accordance with the valid study regulations

The requirements are specified in the respective lectures.

Statistics

Students distinguish qualitative from quantitative methods, and are able to select appropriate methods for a given research question. They can explain and illustrate the underlying ideas of specific methods and their principal areas of application.  

Students can justify the method selection regarding regarding automated collection, screening, processing, analysing, quantifying, interpreting and visualising different kinds of data (e.g., reviews, tweets, forum postings, images, and quantitative data). In addition, they are able to demonstrate deeper pattern discovery skills using various techniques and tools applied to the collected data.

Students are able to critically reflect on the utility, strengths and limitations of the selected methodology within real-world case studies.

Students are able to transfer their knowledge to real-world case studies including the use of appropriate statistical software.

Students are able to diagnose and address questions using data, extract key outcomes, summarise results and implications, produce recommendations and support data-driven decision-making.

Students are able to manage their goals and roles within the group. They can effectively collaborate, plan, organise, prioritise, present, visualise and communicate the analysis outcomes in oral presentations and in comprehensible written reports.

Students are able to critically reflect, question, and communicate the utility and limitations of the applied methods. They are aware of data protection issues and ensure ethical data collection.

This module prepares students for applied data research in any subject area.

• International Management, B.A.

• Markovic-Bredthauer, Danijela

• Markovic-Bredthauer, Danijela