Objectifs

At the end of the course the students will be able to:

• Use conceptual data modeling techniques for database design
• Create business process models based on process mining
• Apply conceptual modelling to business analytics projects

Contenus

The course will focus on using conceptual modeling techniques (UML and ER models, dimensional modelling) at different phases of the business intelligence project. The students become familiar with the structure and semantics of enterprise databases, business process modeling, dimensional modelling, design of statistical databases, and business analytics project design from identifying data sources to reporting results.

During the course the students will create conceptual models using UML and ER techniques, create database models from the conceptual models, model business processes based on process mining using R, and design and implement business analytics projects using databases and common statistical methods in R environment.

Références

No assigned textbook. All relevant material will be covered in lectures and made available on the course website. For those interested, the following books contain material relevant to the course:

• Olivé, A. Conceptual modeling of information systems. Springer Science & Business Media, 2007.
• Holt, Jon. A pragmatic guide to business process modelling. BCS, The Chartered Institute, 2009.
• Kimball, R. and Ross M. The data warehouse toolkit: The definitive guide to dimensional modeling. John Wiley & Sons, 2013.

Evaluation

1ère tentative

Examen:

Sans examen (cf. modalités)  

Evaluation:

No exam. Students will be graded on three assignments, one of each main objective of the course, report the results, and present them in the class.

Rattrapage

Examen:

Sans examen (cf. modalités)  

Evaluation:

Additional assignments.