Code
MGSE STR 4402
Level
M1
Field
Stratégie
Language
Anglais/English
ECTS Credits
3
Class hours
18
Total student load
20
Program Manager(s)
Department
- Management, Marketing et Stratégie
Educational team
Introduction to the module
This Business Intelligence (BI) course equips students with the skills to transform data into actionable insights, essential for strategic decision-making. It covers the BI lifecycle, including data collection, management, analysis, and visualization. The course delves into various BI tools and technologies, emphasizes effective data visualization techniques, and explores real-world BI implementations.
Learning goals/Programme objectives
- LG1 Being able to extend digital intelligence through its different dimensions
Learning objectives/Intended learning outcomes
- 1.3 - Develop competitiveness in business, and digital sovereignty
- 2 - Having the ability to manage uncertainty and complexity with accuracy and rigor
- 2.1 - Identify and analyze in depth problems, causes and impacts
- 2.2 - Explore solutions, decisions, and their relative and absolute impacts
- 2.3 - Identify optimal solution(s) and priorities toward implementation
- 3 - Having the foundations of responsible and sustainable management
- 3.1 - Understand and employ basic concepts, knowledge and theories related to the discipline
- 3.2 - Apply discipline knowledge appropriately and effectively
- 3.4 - Select and employ judiciously appropriate techniques and tools within the discipline
- 4 - Having access to different cross disciplinary management approaches and tools
- 4.2 - Understand and employ cross-disciplinary concepts, knowledge, theories
- 4.3 - Apply cross-disciplinary management approaches and tools effectively and judiciously
- 4.4 - Evaluate the use of cross-disciplinary management approaches and tools
Rubrics
1. Understanding the different types of data: structured, unstructured, semi-structured, and big data.
2. Understanding the different phases: data collection, data integration, data analysis, data visualization, and data interpretation.
3. Learning about BI tools and technologies: data warehouses, ETL processes, dashboards, reporting tools, and data mining techniques.
4. Identifying the numerous challenges at each phase and strategies to overcome them.
5. Identifying the links between technological, social, and business aspects of any BI implementation.
Content : structure and schedule
1. Fundamentals of Business Intelligence and Data Collection
• Introduction to Business Intelligence
• Types and Sources of Data
• Data Collection and Integration
2. Data Analysis Techniques and Tools
• Overview of Data Analysis
• BI Tools and Technologies
3. Data Visualization and Reporting
• Principles of Effective Data Visualization
• Visualization Tools
• Reporting Techniques
4. Implementation, Ethical Considerations, and Integration
• Implementing BI Solutions
• Ethical Considerations and Governance
Sustainable Development Goals
Goal 9 : Industry, innovation, and infrastructure
Goal 12 : Responsible consumption and production
Goal 17 : Partnerships for the goal
Number of SDG's addressed among the 17
3
Learning delivery
Mixte
Pedagogical methods
Along with classes, other pedagogical tools will be used such as class discussion, case studies and group exercises.
Evaluation and grading system and catch up exams
Continuous assessment: 40%
• case studies and exercises in class (20%)
• final project (20 %)
Final assessment: 60%
• At the end of the course, the final exam (written test) assesses if students master the content of the course (concepts, tools...) and can reflect on how it applies in real-life situations.
A catch-up exam (written test) is organized for students who do not pass on their first attempt.
Module Policies
Teacher-learner communication
● The teacher will contact learners via their school email address (IMT-BS/TSP) and the Moodle portal. No communication via personal email addresses will take place. It is the student's responsibility to check their IMT-BS/TSP mailbox regularly.
● Learners can communicate with the teacher by sending an email to his/her institutional address. If necessary, it is possible to meet him in his office during office hours or by appointment.
Learners with accommodation needs
If the learner has a disability that prevents them from completing the work described or requires any kind of accommodation, it is their responsibility to inform the Director of Studies (with supporting documentation) as soon as possible. They should also not hesitate to discuss the matter with their teacher.
Behaviour in class
● As a courtesy to the teacher and other learners, all mobile phones, electronic games or other sound-generating devices must be switched off during lessons.
● The learner must avoid any disruptive and disrespectful behaviour such as: arriving late to class, leaving early, inconsiderate behaviour (e.g. sleeping, reading a document not related to the course, using vulgar language, talking excessively, eating, drinking, etc.). A warning may be given for the first breach of these rules. Offenders will be penalised and may be expelled from the class and/or subject to other disciplinary procedures.
● Tolerated lateness is 5 minutes. Attendance will be declared on Moodle during these 5 minutes via a QR code provided by the teacher at each class start.
● The learner must arrive on time for examinations and other assessments. No one will be allowed into the classroom once the first person has completed the exam and left the room. There are absolutely no exceptions to this rule. No learner may continue to take an exam once the time has elapsed. No learner may leave the room during an exam unless he/she has finished and handed in all the documents.
● In the case of distance learning courses, learners must keep their cameras switched on unless otherwise instructed by the teacher.
Code of ethics
IMT-BS is committed to a policy of honesty in the academic environment. Any conduct that compromises this policy may result in academic and/or disciplinary sanctions. Learners must refrain from cheating, lying, plagiarism and theft. This includes doing original work and acknowledging anyone else whose ideas and printed materials (including those from the internet) are paraphrased or quoted directly. Any learner who violates or assists another student in violating the standards of school behaviour will be sanctioned in accordance with the rules of the IMT-BS.
Textbook Required and Suggested Readings
Sherman, R. (2014). Business intelligence guidebook: From data integration to analytics. Newnes.
Provost, F., & Fawcett, T. (2013). Data Science for Business: What you need to know about data mining and data-analytic thinking. " O'Reilly Media, Inc.".
Keywords
Data Visualization, Descriptive Analytics, Predictive Analytics, Data Mining, Dashboard Design, Data Integration, Business Analytics, Data Governance.
Prerequisites
No specific prerequisite is necessary.