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Summary

The Master's degree programme "Business Informatics" prepares students for challenging and exciting opportunities to carry out research and development work in both the domestic and international markets. Students are taught how to use the conceptual approaches of business informatics to solve business and commercial challenges. Graduates from the M.Sc. programme have not only acquired a thorough grounding in business informatics, economics, computer science and academic and research techniques, they have also demonstrated that they can successfully undertake independent, self-organized learning and can apply appropriate methodological and analytical skills when solving challenging problems. Business informatics graduates from Saarland University are highly sought-after as experts able to transfer ideas and technology from the academic world to the world of commercial business practice.

Business informatics at Saarland University combines the disciplines of economics and informatics and the department collaborates closely with a large number of respected institutions located on the Saarbrücken campus, including the German Research Center for Artificial Intelligence (DFKI) and the Max Planck Institute for Informatics (MPII). The department also maintains fruitful cooperative ties to universities in Australia, the USA and other countries. The staff scientists and research teams in business informatics are engaged in application-driven research projects and in knowledge-sharing activities with academics and scientists in neighbouring disciplines.

Highlights

  • Specializations in BPM, BI or Research
  • Wide choice of courses
  • Master thesis abroad or in companies possible
Schedule Part-time and full-time
Duration 2 Years
Presence of students On-campus and on-line
Scholarships available No

Courses

Lecture

Learning objectives of the course are:

-        Knowledge and ability to describe the central domain-independent and industry-specific processes of an organization

-        Knowledge and understanding of the basic data structures of domain-independent and industry-specific information systems

-        Application of conceptual modeling methods to business-driven problems

 347
Project seminar

This course has the intention to practice collaborative business process management in an international environment using realistic scenarios. For each scenario, a concept for outsourcing parts of the business from an American to a German enterprise has to be developed. This includes organizational rules, a description of collaborative business processes and an IT concept. In each scenario, a group of students from UdS represents a German company and a group of students at Widener University in Chester, Pennsylvania represents an American company.

 391
Lecture

After participating in the course „Controlling with SAP ERP“, students should:

-        Know the basic functions of the standard software SAP ERP

-        Be able to navigate the system

-        Understand the dependencies between the controlling module (CO) and the upstream modules

-        Be able to independently process relevant cost accounting cases in the controlling module (CO)

-        Know the cost-type, cost-center and cost-unit accounting in SAP ERP

-        Know basic controlling analysis functions in SAP ERP

 393
Lecture
The module "Human Resource Information Systems" provides qualifications of EQF level 7: A. Knowledge: comprehensive, highly specialized knowledge of • functionalities and application domains of HRIS • legal conditions • categories and architectures of HRIS • methods and state-of-the-art in technical and managerial research in HRIS B. Skills: comprehensive, highly specialized practical skills in the domains of HRIS selection, implementation, and application C. Competencies: self-directed design and management of complex HRIS related work contexts, especially • selection, implementation and operation of HRIS • application of HRIS for automation, information and strategic transformation of human resource management
 592
Lecture

The module "Management Information Systems I: Data Warehousing" provides qualifications of EQF level 7:

A.     Knowledge: comprehensive, highly specialized knowledge of

a.      Functionality and application domains of data warehousing systems

b.      Categories and system architectures of data warehousing systems

c.      Implementation methods and models for data warehousing systems

d.      Methods and state of the art of technical and managerial data warehousing research

B.     Skills: comprehensive, highly specialized practical skills in the domains

a.      Data warehouse implementation

b.      Data warehouse application

c.      Data warehouse maintenance

C.     Competencies: self-directed design and management of complex Data warehouse related work contexts, especially

a.      Implementation and maintenance of data warehouse systems

b.      Applications of data warehouse systems in organizational business functions

 446
Lecture

The module "Management Information Systems II: Data Mining" provides qualifications of EQF level 7:

A.     Knowledge: comprehensive, highly specialized knowledge of

a.      Functionality and application domains of data mining in management

b.      Data mining procedure models

c.      Categories and architectures of data mining systems

d.      Data preparation and transformation

e.      Data mining algorithms (especially segmentation, classification, association, anomaly detection and assessment)

f.       Methods and state of the art of technical and managerial data mining research

B.     Skills: comprehensive, highly specialized practical skills in the domains

a.      Information demand analysis

b.      Data preparation and transformation

c.      Design and execution of complex analysis processes

d.      Result interpretation and decision support

C.     Competencies: self-directed design and management of complex Data warehouse related work contexts, especially

a.      Implementation and maintenance of data mining systems

b.      Applications of data mining systems for meeting complex information demand in management

 364
Seminar

Process Mining represents the connection between model-based process analyses and data-oriented analysis techniques. New insights into time-related log data can be gained through concepts from the field of data mining and their adaptation to the special features of process data. In this course, both the theoretical basics and the practical application with supporting software tools will be taught.

The course is based on the online course "Process Mining: Data Science in Action" of the Technical University Eindhoven. Over a period of 12 weeks during the semester, the course content is provided to the students in the form of book chapters and videos, which are compiled by the students themselves, with an effort of 2 SWS for learning the content. The theoretical parts are supplemented by two-hour exercises, which take place every two weeks (6 sessions in total). The exercises are focused on the presentation of solutions to the exercise sheets, which are provided at the beginning of each topic block, i. e. the processing time per exercise sheet is 2 weeks. The exercises are worked on individually. Instead of a final exam, each student will work on and present an individual case study. The lecture will be given in English and the tutorial will be held in German. English speaking students are welcome.

 326
Lecture

The course “Value Engineering” extends the former course “Product-Service Information Systems” and offers a systemic view on the design of complex systems. Topics like Design Science, product and service development as well as design and empirical evaluation of hybrid products are scientifically acquired and practically applied in small project groups during the exercise sessions. After participating in this course, the students are able to analyse systems, specify customer demands, execute design processes in teams and empirically validate the resulting designs.

 359
Lecture

Contents of the course „Web Technologies“ are, among others, basics like HTML, CSS and JavaScript/AJAX. Moreover, students get an overview on classical databases in the context of LAMP stack and MVC pattern. NoSQL databases as well as XML/XQuery/XPath and XSLT are covered, along with the topic of semantic data representations, with lower-case semantics, Web Ontology Language (OWL), reasoning and rule-based deduction. The course is concluded with the topics of Big Data and Map/Reduce. All topics are practically applied in weekly exercise sessions.

 385

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