Code
MGFF MIS 5451
Level
M2
Field
Systèmes d’information
Language
Français/French
ECTS Credits
2
Class hours
14
Total student load
20
Program Manager(s)
Department
- Technologies, Information et Management
Introduction to the module
Les données sont au cœur des stratégies des différents acteurs dans la création et /ou captation de valeur. Au-delà des aspects éthiques et des enjeux juridiques autour de la protection des données personnelles, le numérique a conduit à une redéfinition de la place des données (big data, smart data etc.) dans des secteurs variés et à de nouvelles pratiques en matière de management et de gouvernance des données.
Learning objectives/Intended learning outcomes
- 1.1 - Audit advanced and specialised uses of digital intelligence tools in order to deploy them appropriately, taking into account the strategic context of organisations.
Content : structure and schedule
Acculturation
La donnée une mine d'or sous exploitée
Sources de données diverses et variées
Comment identifier les données
Comment surmonter les freins liés à la collecte de données?
Processus Data Processus Data, un processus itératif
Stratégie Data
Statégie Data en pleine évolution
Illustration des concepts Data Driven et Data Centric
Enjeux, menaces, facteurs de risque et bonnes pratiques
Evaluation de la maturité de la Data (ouverture sur un dialogue)
Se mettre en conformité tout en tirant de la valeur des données
Les Parties prenantes de la Data Les postes dans la Data ne sont pas uniquement des rôles techniques, illustration
La gouvernance des données
Composante de l'analytique Analyse cognitive, prédictive, prescriptive, diagnostique, descriptive
Data Preparation Présentation de la Data Preparation
Data Vizualisation Présentation de la Data Vizualisation
Construire de bons indicateurs
Démystification Démystification des Buzzwords de la Data
Cas d’usage Présentation de cas d'usage
Comment identifier des cas d'usage
Brainstorming sur les cas d'usage
Qualité des données Critères de qualité de données et illustration
La perception de la qualité des données
Comment s'assurer de l'exhaustivité des données
Cas pratiques Cas pratiques Alteryx
Cas pratiques Power BI
Number of SDG's addressed among the 17
1
Learning delivery
synchrone
Pedagogical methods
Ce module intègre des éléments "théoriques" ainsi que des mises en situation :
Cours (Acculturation Data et principes de gouvernance)
Cas pratiques
Manipulation de logiciels (Alteryx, Power BI)
Evaluation and grading system and catch up exams
Le CF1 correspond (renvoie) à un ensemble d'activités qui donnent lieu à une note individuelle et collective.
Il se décompose en trois blocs :
Présence et participation à toutes les séances (20%)
Participation aux exercices/travaux pratiques (logiciel Alteryx) pendant les séances (30%)
Restitution orale au cours de la dernière séance (évaluations individuelles et collectives) : 50%
Rattrapage : CF2 - Examen sur table (1h30)
En cas de non validation du CF2, une prolongation de scolarité pourra être prononcée par le jury des études
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
Supports de cours Forvis Mazars
Keywords
Data, acculturation, gouvernance, stratégie, processus, data visualisation
Prerequisites
M1