Learning outcomes

By the end of this course, students will be able to:
 
1. Understand the importance and challenges of information systems modeling.
2. Know the basic concepts of information systems modeling.
3. Define the concept of data modeling and its significance for information systems.
4. Define and compare three types of data models (conceptual, logical, physical).
5. Based on natural language requirements, create an Extended Entity-Relationship model representing the data layer of an information system (using PlantUML and on paper).
6. Transform an Extended Entity-Relationship model into a normalized logical Relational model (represented on paper and with DBML).
7. Justify design choices in the creation and transformation of models when multiple options are available.
8. Evaluate the quality of a data model.
9. Choose (with justification) between several alternative data models for a given information system.
10. Normalize relational models.
11. Master the basic concepts of data governance and data quality.
12. Develop information systems models using UML diagrams.
13. Integrate different UML models in complex projects.
14. Use modeling tools like PlantUML and DBML.

Goals

The objectives of this course are to:
 
1. Provide an in-depth understanding of information systems and data modeling techniques.
2. Develop the skills necessary to use modeling tools to create and manage information system models.
3. Prepare students to analyze and improve the quality of data models and their governance.
4. Train students in the use of UML, Entity-Relationship, and Relational diagrams for designing complex information systems.

Content

1. General Introduction to Information Systems Modeling Practice.
2. Introduction to Data Modeling.
3. Conceptual Data Modeling (Extended Entity-Relationship Language).
4. Logical and Physical Modeling (Relational Language, Conversion, and Normalization).
5. Advanced Topics in Data Modeling (Quality, Standards, and Governance).
6. Use Case Diagrams.
7. Activity Diagrams.
8. Class Diagrams 1.
9. Class Diagrams 2.
10. Sequence Diagrams.
11. State Diagrams.
12. Integration of UML Models.

Assessment method

Exam: Final written assessment with theoretical and practical questions and exercises, including a case study.

Sources, references and any support material

  • Charroux, B., Osmani, A., & Thierry-Mieg, Y. (2010). UML 2: pratique de la modélisation. Paris: Pearson Education.
  • Roques, P. (2018). UML 2.5 par la pratique: Etudes de cas et exercices corrigés. Editions Eyrolles.
  • https://www.uml.org
  • PlantUML
  • DBML
  • Snoeck, M. (2014). Enterprise information systems engineering. The MERODE Approach. Springer
  • Allen, S. L., & Terry, E. (2006). Beginning relational data modeling. Apress.
  • Simsion, G., & Witt, G. (2004). Data modeling essentials. Elsevier.

Language of instruction

Français
Training Study programme Block Credits Mandatory
Bachelor in Business Engineering Standard 0 3
Bachelor in Business Engineering Standard 3 3