Short description
The course covers conceptual foundations, implementation, and operations of Business Intelligence solutions. Students will learn how to design and operate data warehouses, reports and dashboards, based on SAP BW, SAP BusinessObjects, as well as SAP HANA.

Topics

• Conceptual foundations of data warehouses and on-line analytical processing (OLAP)
• Conceptual foundations of in-memory column-based databases
• SAP BW Data Modeling & ETL
• SAP Business Explorer
• SAP BusinessObjects Cloud and Enterprise
• In-Memory Computing with SAP HANA

Learning objectives

• Students know and understand foundational concepts and methods of data warehousing and on-line analytical processing (OLAP)
• Students know and understand foundational concepts and methods of in-memory column-based databases
• Students extract, transform, and load data from transactional systems into business intelligence solutions
• Students design and develop business intelligence reports and dashboards

Methods

• The module integrates theoretical knowledge and practical skills in an interactive seminar.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Compulsory reading

• Egger et al. (2007). SAP Business Intelligence, SAP Press (ISBN: 978-1-59229-082-6)
• Plattner, H. (2009). A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database, Hasso Plattner Institute for IT Systems Engineering University of Potsdam.
• Inmon, W. H. (2005). Building the Data Warehouse, (4th ed) John Wiley.
• http://help.sap.com/pcat_analytics

Further reading

• Egger et al. (2009). Reporting und Analyse mit SAP BusinessObjects, Galileo Press. (ISBN: 978-3-8362-1380-6).
• Codd, E.F. et al. (1993). Providing OLAP (Online Analytical Processing) to User-Analysts: An IT Mandate, White Paper im Auftrag von Arbor Software (jetzt Hyperion Solutions). Siehe auch: http://www.fpm.com/refer/codd.html.
• Egger N., Fiechter J.-M. & Rohlf J. (2005). SAP BW - Data Modeling, SAP Press (ISBN: 1-59229-043-4)
• Plattner, H. & Zeier, A. (2011). In-Memory Data Management. An Inflection Point for Enterprise Applications, Springer, ISBN-13: 9783642193620
• Hichert, R. & Moritz, M. (1995). Management-Informationssysteme. Praktische Anwendungen, (2nd ed.) Springer Verlag.
• Kaiser, B.-U. (1999). Unternehmensinformation mit SAP-EIS. Hrsg. von Stephen Fedtke, Vieweg.
• Keen, P. G. W. (1978). Decision support systems: an organizational perspective. Reading, Mass., Addison-Wesley Pub. Co. ISBN 0-201-03667-3
• Salmeron, Jose L. (2003). EIS Success: Keys and difficulties in major companies. Technovation, 23 (1), 35–38.

Short description
The course covers the complete modern data management cycle, with a focus on collecting data from diverse sources and preparing it to enable data-driven applications. Students will learn how to handle various data formats, assess and eventually improve data quality, and store as well as process data using SQL, NoSQL, and Hadoop technologies. The course will also look into the basics of mining (big) data sets.

Topics

• Modern data management requirements
• Database system architecture
• Diagnosing and handling data quality problems
• Relational databases (SQL)
• Hands-on labs with MySQL
• Concurrency control techniques
• NoSQL databases (e.g., MongoDB)
• Apache Hadoop (HDFS, MapReduce)

Learning objectives

• Students will acquire and understand foundational concepts and methods of modern data management
• Students will collect and prepare data in order enable data-driven applications
• Students will select and apply appropriate technologies for building data-driven applications

Methods

• The module integrates theoretical knowledge and practical skills in an interactive lecture.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Recommended previous knowledge

• Module “Process and Data Management”

Compulsory reading

• Elmasri, R., & Navathe, S.B. (2016). Fundamentals of Database Systems, 7th edition. New York: Pearson Education.
• Harrison, G. (2015). Next Generation Databases – NoSQL, NewSQL, and Big Data. California: Apress Media

Short description
The course focuses on developing research proposals in the field of business process management.

Topics

• Conducting literature reviews
• Developing research questions
• Designing qualitative, quantitative, and design oriented research
• Writing research proposals
• Ethical issues in business process management research

Learning objectives

• Students will know the professional code of conduct of the academic IS discipline.
• Students will effectively communicate academic research designs.
• Students will produce rigorous research proposals in the area of business process management.
• Students will recognize and analyze ethical problems of designing and conducting research in the field of business process management.

Methods

• The module integrates theoretical knowledge and practical skills in an interactive seminar.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Recommended previous knowledge

• Research Methods

Compulsory reading

• Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage.

Further reading

• Kumar, R. (2014). Research methodology: A step-by-step guide for beginners. London, UK: Sage Publications.
• Recker, J. (2012). Scientific Research in Information Systems: A Beginner’s Guide. Springer, Heidelberg, Germany.

Short description
Process management refers to the operation, improvement and innovation of business processes. In the course, students apply fundamental frameworks, models, and methods in process management.

Topics

• Business process operation
• Business process change
• Strategic alignment
• Governance
• Quality management
• Six sigma
• Process management skills
• Organizational culture

Learning objectives

• Students will analyze a real-world case of a specific industry through the lens of process management knowledge.
• Students will integrate knowledge to identify areas of improvement or innovation.
• Students will use appropriate methods to develop recommendations for a case company.
• Students will identify and define meaningful skill sets for seminar groups.

Methods

• The module integrates theoretical knowledge and practical skills in a seminar focusing on a real-world case.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Short description
Process management refers to the operation, improvement and innovation of business processes. The course covers fundamental frameworks, models, and methods in process management.

Topics

• Business process operation
• Business process change
• Strategic alignment
• Governance
• Quality management
• Six sigma
• Process management skills
• Organizational culture

Learning objectives

• Students will know the foundations and the emergence of process management (e.g. business process re-engineering, total quality management).
• Students will understand the goals of process management (e.g. time, cost, quality, sustainability).
• Students will be able to apply the core elements of process management (strategic alignment, governance, methods, technologies, people, culture).
• Students will integrate knowledge to understand the benefits and competitive advantages of a holistic process management approach.
• Students will know key principles of good process management.

Methods

• The module integrates theoretical knowledge and practical skills based on an interactive lecture.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Compulsory reading

• The students will be provided with the lecture slides and supporting materials throughout the course.

Further reading

• vom Brocke, J., & Rosemann, M. (Eds.). (2010). Handbook on business process management. Berlin: Springer.

Short description
The course covers conceptual foundations, methods, and technologies for implementing and managing business processes with the help of IT. In particular, students will learn how to automate and monitor software-based business processes and mine process execution logs.

Topics

• Foundations of process automation
• Workflow management systems (e.g., YAWL)
• Process mining (e.g., ProM)

Learning objectives

• Students know and understand foundational concepts and methods of process automation (workflow management)
• Students know and understand foundational concepts and methods of process mining
• Students design and develop executable business processes
• Students apply analytical techniques to mine business process logs

Methods
The module integrates theoretical knowledge and practical skills based on an interactive lecture. The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Compulsory reading

• Dumas, M., La Rosa, M., Mendling, J., Reijers, H. (2013). Fundamentals of Business Process Management. Berlin: Springer.
• Russell, N., Van Der Aalst, W., Ter Hofstede, A. (2016): Workflow Patterns: The Definitive Guide. Cambridge, MIT Press.

Further reading

• Ter Hofstede, A., Van der Aalst, W., Adams, M., Russell, N. (2010). Modern Business Process Automation. Berlin: Springer.
• Van der Aalst, W. (2011). Process Mining: Discovery, Conformance and Enhancement of Business Processes. Berlin: Springer.

Short description
The course focuses on process analysis, including approaches and methods for designing, analyzing and simulating processes in organizations.

Topics

• Introduction to process analysis
• Process modeling and design
• Process flow analysis
• Process simulation

Learning objectives

• Students will know how processes can be modeled, analyzed, and simulated.
• Students will know basic methods of process modeling in order to analyze, design, and implement information systems in organizations.
• Students will use methods of process flow analysis and simulation in order to analyze, design, and improve business processes in organizations

Methods

• The module integrates theoretical knowledge and practical skills in an interactive lecture.
• The e-learning platform Moodle will be used throughout the course for the dissemination of course material and discussions.

Entry requirements

• none

Compulsory reading

• Laguna, M. & Marklund, J. (2013): Business Process Modeling, Simulation and Design, CRC Press: Boca Raton.

Further reading

• vom Brocke, J. & Rosemann, M. (Eds.) (2014). Handbook of Business Process Management. Springer: New York.

Das Modul Masterthesis setzt sich zusammen aus:
a) der Masterthesis

b) dem Kolloquium zur Masterthesis
Das Kolloquium dient zur Überprüfung des bisherigen Fortschritts und der Statusermittlung. Das Kolloquium wird als Einzelpräsentation mündlich durchgeführt und dauert 30 Minuten.
Im Kolloquium wird eine Präsentation durchgeführt, in der die Forschungsfrage und der Weg zur Problemlösung vorgestellt werden. Die Präsentation soll in der Struktur mit der Schlusspräsentation vergleichbar sein. Am Ende der Präsentation können offene Fragen besprochen werden.
Für das Kolloquium werden Gruppen gebildet. Alle Teilnehmer der Gruppe sind von Beginn bis zum Schluss der Präsentation der Gruppenmitglieder anwesend. Folgende Unterlagen sind mitzubringen:
1. Eingereichtes Exposé (1 Exemplar für Gutachter)
2. Aktuelles Inhaltsverzeichnis (1 Exemplar für Gutachter)
3. Folien der Präsentation (5-6 Exemplare für Studienleiter, Gutachter und Gruppenmitglieder)
4. Fragebogen/Interviewleitfaden (5-6 Exemplare für Studienleiter, Gutachter und Gruppenmitglieder)
5. Aktuelles Literaturverzeichnis (1 Exemplar für Gutachter)

c) der Präsentation und Verteidigung der Masterthesis
In der Präsentation und Verteidigung der Masterthesis weist der Studierende die Befähigung wissenschaftlicher Arbeitsweise sowie die für die Ausübung des Berufes erforderlichen fachlichen Kompetenzen und Kommunikationsfähigkeiten nach.

In der Masterthesis wird ein studiengangsspezifisches Problem auf wissenschaftlicher Grundlage selbständig erarbeitet.

Kolloquium
Das Kolloquium zur Masterthesis dient der Prüfung der Authentizität sowie der Ermittlung des Fortschrittes der Arbeit.
Bei Nichtbestehen des Kolloquiums kann die Masterthesis nicht weiter bearbeitet werden. Die Modulprüfung gilt als nicht bestanden. Ein neues Exposé kann eingereicht werden.

Präsentation und Verteidigung der Masterthesis
Die Präsentation und Verteidigung dauert maximal 45 Minuten und ist öffentlich.
Die Benotung der Master-Thesis setzt sich aus der Note für die schriftliche Arbeit und der Note für die Präsentation und Verteidigung im Verhältnis 70 zu 30 zusammen.
Hat der Studierende die Master-Thesis nicht bestanden, so kann er dieses Modul frühestens zum nächstmöglichen Prüfungstermin wiederholen. Eine zweite Wiederholung ist nicht möglich und das Masterstudium gilt als endgültig nicht bestanden.

Erfolgreicher Abschluss der Module "Start-Up-Lab - Part I" und "Start-Up-Lab - Part II"