Actualités et agenda
Nos formations
Établissement
Langue d'enseignement
English
Matières
MANAGEMENT OF INFORMATION SYSTEMS
Ce cours apparaît dans les formation(s) suivante(s)
MSc in Big Data Analytics for Business
- Crédits ECTS: 4.00
Responsable(s)
A.DE CAIGNY
Intervenant(s)
Arno DE CAIGNY
Présentation
Prérequis
None
Objectifs
At the end of the course, the student should be able to:
- be knowledgeable about the commercial analytical tools in business
- extract, manipulate, analyze and report data using SAS/Base & SAS/Macro
- detect the advantages and disadvantages of using an open source analytical tool
- find solutions for complex (coding) tasks within intercultural teams
These competencies and/or skills contribute to the following learning objectives
- 1.B Successfully collaborate within a intercultural team
- 3.A Breakdown complex organizational problems using the appropriate methodology
- 5.B Construct expert knowledge from cutting-edge information
- 7.A Demonstrate an expertise on key concepts, techniques and trends in their professional field
- 7.B Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field
- 7.D Be a reference point for expertise-related questions and ambiguities
- be knowledgeable about the commercial analytical tools in business
- extract, manipulate, analyze and report data using SAS/Base & SAS/Macro
- detect the advantages and disadvantages of using an open source analytical tool
- find solutions for complex (coding) tasks within intercultural teams
These competencies and/or skills contribute to the following learning objectives
- 1.B Successfully collaborate within a intercultural team
- 3.A Breakdown complex organizational problems using the appropriate methodology
- 5.B Construct expert knowledge from cutting-edge information
- 7.A Demonstrate an expertise on key concepts, techniques and trends in their professional field
- 7.B Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field
- 7.D Be a reference point for expertise-related questions and ambiguities
Présentation
- Run SAS programs in a PC environment
* Read raw input files in various formats and create SAS datasets
* Create new variables in the data step
* Use SAS procedures to describe data numerically and graphically
* Annotate SAS output with informative titles, labels, and formats
* Work with SAS datasets: sort, subset, merge, and re-format SAS datasets
* Use SAS procedures scripts for basic statistical inference
* Export SAS data and output to other computers and software
* Read raw input files in various formats and create SAS datasets
* Create new variables in the data step
* Use SAS procedures to describe data numerically and graphically
* Annotate SAS output with informative titles, labels, and formats
* Work with SAS datasets: sort, subset, merge, and re-format SAS datasets
* Use SAS procedures scripts for basic statistical inference
* Export SAS data and output to other computers and software
Modalités
Organisation
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours magistral | 24,00 | ||
| Travail personnel | |||
| Group Project | 25,00 | ||
| Charge de travail personnel indicative | 26,00 | ||
| Overall student workload | 75,00 | ||
Évaluation
Details will be given in the first class.
| Control type | Duration | Amount | Weighting |
|---|---|---|---|
| Contrôle continu | |||
| Participation | 0,00 | 1 | 10,00 |
| Autres | |||
| Rapport écrit | 4,00 | 1 | 40,00 |
| Projet Individuel | 4,00 | 1 | 50,00 |
| TOTAL | 100,00 | ||
Ressources
Bibliographie
The Little SAS Book: A primer: Fifth Edition, L. Delwiche, S. Slaughter, SAS Institute -