Faculty of Agricultural Science and Landscape Architecture
Version 13.0 of 08/06/2019
- Code of Module
- Modulename (german)
- Study Programmes
Wirtschaftsingenieurwesen Agrar/Lebensmittel (B.Eng.)
- Level of Module
- Mission Statement
With the increasing digitalization of products, services and processes in the business context but also in our private lives, more and more data is produced every day. This poses challenges to companies, who want to derive insights from that data to improve their decision-making processes. In this course, the students learn what data is and how it is created. The students learn how to model data, work with databases to manage data, and how to write SQL queries to answer questions with data. Moreover, the students acquire important concepts for a systematic data-driven decision process.
1 Basics of Data
2 Data Modeling
4 Query Data with SQL
5 Corporate Business Intelligence
- Learning Outcomes
The students know what data is and how it is stored and processed in a computer.
The students understand why it is important for companies to manage data.
The students know the basic concepts of a database management system.
The students know the components and architecture of corporate business intelligence solutions.
The students understand the principles of the relational database.
The students understand the differences between structured and semi / unstructured data.
Instrumental Skills and Competences
The students can apply data modeling techniques.
The students can read and explain given data models.
The students can write SQL queries to answer questions with a given data set.
Communicative Skills and Competences
The students can formulate hypothesis that can be verified with a given data set.
The students have acquired and deepened their capability to precisely present their ideas and results in front of a group.
Systemic Skills and Competences
The students query relational databases in order to answer questions with data.
- Mode of Delivery
The course follows the flipped classroom concept. Material such as audio, video and literature are provided before each session. The students are expected to prepare for class with the recommended material. The time in class will mainly be used to work in small groups and to deepen the understanding, knowledge, and acquired skills.
- Expected Knowledge and/or Competences
No particular prerequisites.
- Responsible of the Module
- Concept of Study and Teaching
Workload Dozentengebunden Std. Workload Lehrtyp 10 Vorlesungen 40 Übungen 5 Prüfungen Workload Dozentenungebunden Std. Workload Lehrtyp 30 Kleingruppen 45 Veranstaltungsvor-/-nachbereitung 20 Prüfungsvorbereitung
- Recommended Reading
Will be announced during the course.
- Graded Exam
- Portfolio exam
- Two-Hour Written Examination
- Viva Voce
- Assessment Methods Remark
Standard exam performance: Portfolio;Partial performances in portfolio examination:Multiple-Choice-Exam - 15%Multiple-Choice-Exam - 15%Case Study, written - 70%
- Module Frequency
Only Winter Term
- Language of Instruction