Code
MGFE MIS 5206
Level
M2
Field
Systèmes d’information
Language
Anglais/English
ECTS Credits
4
Class hours
38
Total student load
75
Program Manager(s)
Department
- Technologies, Information et Management
Introduction to the module
This course equips students with the concepts, frameworks, and practical skills needed to establish and operate effective data governance programs in organizations. It blends strategic, organizational, and technical perspectives to ensure that data assets are managed responsibly, reliably, and in alignment with business goals and regulatory requirements. It focuses on the professional standards (e.g., DAMA & DMBOK) for initiating a data governance program including aspects about data quality governance and how it can be evaluated and aligned with business needs of organizations for value generation.
In this course, students will learn how to:
- Define data governance principles, policies, roles, and responsibilities (e.g., data owners, stewards, and custodians);
- Design governance frameworks and operating models that align with organizational structure and culture;
- Develop data standards, quality metrics, and metadata management practices;
- Implement processes for data lifecycle management, including classification, access control, compliance, and security;
- Evaluate governance maturity and measure performance through key indicators;
- Address ethical, legal, and regulatory considerations (e.g., GDPR, data privacy, and risk management).
The course emphasizes case studies, real-world scenarios, collaborative design exercises, and tool-based implementation planning. By the end, students should be able to craft a comprehensive governance roadmap tailored to organizational needs.
Learning goals/Programme objectives
- 1. S’approprier les usages avancés et spécialisés des outils de l’intelligence digitale en s’assurant de leur impact durable et responsable,2. Produire et mobiliser des savoirs hautement spécialisés, issus d’une réflexion critique, et dans un champ d’expertise,3. Communiquer stratégiquement dans des environnements globaux et multiculturels,4. Conduire des projets de transformation sociétale, numérique, énergétique et/ou environnementale des organisations
Objectifs d'apprentissage
- 1.2 - Use digital intelligence tools efficiently to support the societal, digital, energy and environmental transformations of organisations, ensuring their sustainable and responsible impact.
Content : structure and schedule
- Data governance principles, policies, roles, and responsibilities (e.g., data owners, stewards, and custodians);
- Governance frameworks and operating models
- Data standards, quality metrics, and metadata management practices;
- Data lifecycle management, including classification, access control, compliance, and security;
- Governance maturity and measure performance through key indicators;
- Ethical, legal, and regulatory considerations (e.g., GDPR, data privacy, and risk management).
- Data lifecycle management via the platform Alteryx (https://www.alteryx.com/)
Sustainable Development Goals
Goal 9 - Industry, innovation and infrastructure
The course teaches advanced techniques and tools for developing innovative data-based solutions in all sorts of industries
Learning delivery
synchrone
Pedagogical methods
Lectures
Practice exercises
Case study development and presentation
Evaluation and grading system and catch up exams
Group projects development and presentation
Catch-up exam via a 3h case study
Module Policies
Professor-Student Communication
● The professor will contact the students through their school email address (IMT-BS/TSP) and the Moodle portal. No communication via personal email addresses will take place. It is the student responsibility to regularly check their IMT-BS/TSP mailbox.
● Students can communicate with the professor by emailing him/her to his institutional address. If necessary, it is possible to meet the professor in his office during office-hours or by appointment.
Students with accommodation needs
If a student has a disability that will prevent from completing the described work or require any kind of accommodation, he may inform the program director (with supporting documents) as soon as possible. Also, students are encouraged to discuss it with the professor.
Class behavior
● Out of courtesy for the professor and classmates, all mobile phones, electronic games or other devices that generate sound should be turned off during class.
● Students should avoid disruptive and disrespectful behavior such as: arriving late, leaving early, careless behavior (e.g. sleeping, reading a non-course material, using vulgar language, over-speaking, eating, drinking, etc.). A warning may be given on the first infraction of these rules. Repeated violators will be penalized and may face expulsion from the class and/or other disciplinary proceedings.
● The tolerated delay is 5 minutes. Attendance will be declared on Moodle during these 5 minutes via a QR code provided by the teacher at each course start.
● Student should arrive on time for exams and other assessments. No one will be allowed to enter the classroom once the first person has finished the exam and left the room. There is absolutely no exception to this rule. No student can continue to take an exam once the time is up. No student may leave the room during an examination unless he / she has finished and handed over all the documents.
● In the case of remote learning, the student must keep his camera on unless instructed otherwise by the professor.
Honor code
IMT-BS is committed to a policy of honesty in the academic community. Conduct that compromises this policy may result in academic and / or disciplinary sanctions. Students must refrain from cheating, lying, plagiarizing and stealing. This includes completing your own original work and giving credit to any other person whose ideas and printed materials (including those from the Internet) are paraphrased or quoted directly. Any student who violates or helps another student violate academic behavior standards will be penalized according to IMT-BS rules.
Textbook Required and Suggested Readings
Ladley, J. (2012). Data Governance : How to Design, Deploy and Sustain an Effective Data Governance Program. Morgan Kaufmann.
Alteryx academy : https://academy.alteryx.com/learn
Keywords
Data governance; DAMA DAMBOK; Data and Value
Prerequisites
Data analytics and AI fundamentals