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| INFO0934-8 | Management Information Systems
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| Duration : | 45h Th |
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| Lecturer : | Ashwin Ittoo |
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Language(s) of instruction :
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| English language |
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Organisation and examination :
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| Teaching in the first semester, review in January |
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Course contents :
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| Information Systems (IS) are systems that encapsulate both the technical aspects of Information Technology (IT) as well as the social ecosystem, such as society or companies, within which the technology is embedded. It has been widely established, both from practical experience and from theoretical studies, that the proper management of IS (MIS) is one of the key determinants that enables organizations to acquire a competitive edge.
The aim of this course is to equip students with the fundamental skillsets in MIS for their future professional (e.g. consultants, managers) or academic (e.g. doctorate) careers. It addresses the topic of MIS by adopting both a theoretical and practical perspective. Students will be exposed to classical themes in MIS, such as Enterprise Resource Planning, as well as to novel issues, such as Data Analytics. In addition, practical sessions will enable them to acquire hands-on experience with a real-life Enterprise Resource Planning systems and in fundamental Java programming.
We will start with a type of IS known as Enterprise Resource Planning (ERP) systems, which are now considered as de-facto in most manufacturing organizations. We will discuss, among others,
- Issues with legacy IS (information silos) and the need for ERP systems
- Opportunities and challenges that organizations face with ERP systems
- Mitigating the failure risks and high costs that are associated with ERP implementations
- Critical success factors and cultural factors that can make or break ERP projects
- Relevant examples from (discrete) manufacturing and real-life ERP implementations will be provided to illustrate the topics covered.
Next, we delve into data modeling using the UML notation.
Subsequently, we will move on to the very relevant topic of Data Analytics.Topics to be covered will include:
- Data Mining applications, e.g. predicting customer profile and purchasing behavior, market segmentation.
- Data Cleaning and Pre-processing
- Data Mining techniques (Classification using Decision Trees, and if time permits, Naive-Bayes)
Practical Session
In addition to the aforementioned theoretical contents, the course will also have separate practical sessions, for the students to put into practice and reinforce what they have learnt during the lessons. The topics during the practical will be as follows:
- Java programming
- ERP practical using SAP
- UML Data Modeling using Modelio (Modelio is an open-source software)
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Learning outcomes of the course :
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| At the end of this course, students should be able to:
- Appreciate the need for integrated Enterprise IS (e.g. ERP) compared to legacy information silos
- Acquire basic hands-on experience with a real-life ERP system, namely SAP
- Implement simple applications/programs using Java and SQL databases (MySQL will be used)
- Describe the ERP implementation process
- Appreciate the risks and challenges of ERP implementations
- Discuss solutions to mitigate the risks and challenges
- Describe the critical success factors of ERP implementation
- Appreciate the importance of user-training and knowledge transfer at the end of the implementation
- Understand the fundamentals of Data Mining techniques (classification, association rules mining, clustering)
- Describe the strengths and weaknesses, and suitable applications for the various techniques
- Appreciate the need for more advanced analytics solution (web mining, text mining)
- Develop a simple analytics program that mines information from the web (in Java)
- Discuss the challenges and opportunities of new trends and technologies in IS
- Discuss how these trends and technologies will affect classical IS like ERPs and society
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Course candidates should have taken (and passed) IS courses of their earlier years, in particular, INFO0076-1: Informatique pour ingénieurs de gestion |
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Planned learning activities and teaching methods :
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Mode of delivery (face-to-face ; distance-learning) :
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- Lectures
- Practical sessions in computer rooms
- Please note that attendance is compulsory for lectures and practical. Please contact the lecturer beforehand if you are unable to attend a lecture or practical
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Recommended or required readings :
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| Selected chapters from
- Enterprise Systems for Management, by Motiwalla and Thompson, Pearson 2012**
- Integrated Business Processes with ERP Systems, by Magal and Word, Wiley, 2012
- Web Data Mining - Exploring Hyperlinks, Contents and Usage Data by Liu Bing, Springer, 2011
- Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, by Linoff and Berry, Wiley 2011
**: main textbook; the others are only recommended readings
- Lecture notes will be provided by the lecturer, and will be available on the LOL@ learning system (http://lola.hec.ulg.ac.be)
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Assessment methods and criteria :
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| The course will follow a continuous assessment system. The final grade will be based on a series of assignments during the course and a final written examination. Details:
- Java programming assignment (practical)
- Text analytics assignment (practical - project based)
- Small written exercise or practical on SAP (to be confirmed)
- Written examination
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Work placement(s) :
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Organizational remarks :
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Contacts :
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| Ashwin Ittoo
HEC Management School - University of Liege |
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| Items online : |
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| http://newlola.hec.ulg.ac.be/course/view.php?id=116 |
| http://newlola.hec.ulg.ac.be/course/view.php?id=116 |
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