Big Data Analytics
Faculty of Agricultural Science and Landscape Architecture
Version 13.0 of 09/06/2019
- Code of Module
- Modulename (german)
Big Data Analytics
- Study Programmes
- Agrar- und Lebensmittelwirtschaft (M.Eng.)
- Angewandte Nutztier- und Pflanzenwissenschaften (M.Sc.)
- Level of Module
- Mission Statement
The progressive digitization of products, services and processes is creating ever-increasing amounts of data. At the same time, the data is very diverse in its kind. In analyzing data, companies have great potential for better and more sustainable decisions. However, at the same time the quantity and diversity poses great challenges for the companies. In this module, students learn methods and technologies in order to successfully cope with these challenges.
Principals of Big Data Analytics Management of Big Data Use of Big Data
- Learning Outcomes
The students know the essential characteristics of big data, and are aware of the challenge of analyzing big data. They are familiar with methods and technologies for dealing with big data.
Students know the differences between structured and unstructured data. In addition to the relational database, students are familiar with new forms of databases that can be used with unstructured data.
Instrumental Skills and Competences
Students use technologies from the big data environment to manage and evaluate large amounts of data. They classify unknown data based on important characteristics and select meaningful procedures and technologies for processing and analysis.
Communicative Skills and Competences
The students extract important insights from a confusing amount of data to answer questions and prepare the results in an appropriate way. They present analysis results in an appropriate manner and aligned to the respective target group.
Systemic Skills and Competences
The students use methods and tools in the company to generate added value from previously unknown data.
- Mode of Delivery
- Expected Knowledge and/or Competences
It is recommended the module "Information Management" of the Bachelor degree. Alternatively or in addition, the module "Applied Analytics" from the Bachelor is useful. The event can also be attended without prior knowledge. In this case, an independent training by means of provided materials is required.
- Responsible of the Module
- Concept of Study and Teaching
Workload Dozentengebunden Std. Workload Lehrtyp 10 others 40 others 5 others Workload Dozentenungebunden Std. Workload Lehrtyp 30 others 45 others 20 others
- Recommended Reading
Wird in der Veranstaltung bekannt gegeben.
- Graded Exam
- Portfolio exam
- Two-Hour Written Examination
- Viva Voce
- Ungraded Exam
- Assessment Methods Remark
Grading in the portfolio:Case study, written (FSS) - 70%Answer-Voting Procedure (AWV) - 15%Answer-Voting Procedure (AWV) - 15%Regular participation (RT) - ungraded
- Module Frequency
Only Summer Term
- Language of Instruction
German and English