Data based management (S2)

Catalog of Institut Mines-Télécom Business School courses

Code

MUSF MIS 2201

Level

L2

Field

Systèmes d’information

Language

Anglais/English

ECTS Credits

3

Class hours

20

Total student load

40

Program Manager(s)

Department

  • Service Bachelor
  • Technologies, Information et Management

Educational team

Introduction to the module

The aim of this course is to make learners aware of the value of data in business and the best practices for managing and protecting it.
Learners acquire a high-level vision of data in the business environment. This will enable them to make a difference in business by considering data as an intangible asset, and to contribute effectively to its enhancement and protection.

Learning goals/Programme objectives

  • LG1 Being able to extend digital intelligence through its different dimensions
  • LG2 Having the ability to manage uncertainty and complexity with accuracy and rigor
  • LG4 Having access to different cross disciplinary management approaches and tools

Learning objectives/Intended learning outcomes

  • 1.1 - Develop digital citizenship and prosperity
  • 1.2 - Develop digital creativity for the individual and the organizational
  • 1.3 - Develop competitiveness in business, and digital sovereignty
  • 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
  • 2.4 - Implement a plan, prepare for changes, and measure the success of actions with regard to strategy and stakeholder
  • 3.4 - Select and employ judiciously appropriate techniques and tools within the discipline
  • 4.3 - Apply cross-disciplinary management approaches and tools effectively and judiciously
  • 4.4 - Evaluate the use of cross-disciplinary management approaches and tools
  • 5.3 - Communicate and collaborate in different contexts
  • 5.4 - Continually leverage skills and knowledge across borders and cultures

Rubrics

L'utilisation des bases de données est un point particulier du numérique/digital. Les apprenants apprennent ici une base de données, et sont sensibilisés à la valorisation de données et à l’intelligence artificielle.

The use of databases is a particular point of digital. Here, learners learn about databases, data enhancement and artificial intelligence.

Content : structure and schedule

The following topics are covered:
- definition of data in the enterprise
- Use and value of data in the enterprise
- Data-related risks
- Data description models
- Data management
- Data protection
- Regulatory constraints on data

Session 1. Definitions and principles of data management: Introductory session, presenting what data is, and how it fits into the enterprise. Demonstration of the value of data. Brief presentation of the organization of a company and the qualities of data for the organization;
 Intersessional work 1: reflection on the risks associated with data and threats to data protection, based on practical examples.

Session 2. Data and its environment : Data is placed in an economic context (monetary value of data). How data is sold, how it is bought, what type of data, etc. (Artificial Intelligence, Big Data).
Intersession 2: Preparing for the next session by reflecting on how learners should manage data, protect it and share it. Reflection on the IT concepts covered in the next session.

Session 3. Computers and data : Debriefing of the previous intersession. Infrastructure in the cloud (for managers, it's very important to have at least one notion, because if they don't know anything about it, they'll be at a loss when they arrive at the company. Precise data vocabulary).
Intersession 3: Exercise on a use case chosen by the learner. Decision on a database to be processed, proposal of databases "if I had a company, I'd do it like this".

Session 4. Practical work: Review and progression of work on the learner's case carried out during the previous intersessional work, including a short presentation of learners who wish to talk about their case, or presentation of original cases chosen by the learners. A much more detailed session on database management, a practical case used in the teacher's own company.
Intersession 4: Resume the database proposed in the previous intersession, and correct the work following the course given today, with more details, improvements, etc.

Session 5. The uses of data: Correction of the exercise from the previous intersession. Several points addressed here: 1-How to use data in concrete terms (several algorithmic solutions, etc.)
2-Environmental aspects of data. What is the energy consumption of an e-mail, for example?
Intersession 5: Exercise covering all the concepts seen in class and how learners will deal with the issues during the exam. Encouragement to contact the teacher to ask questions about any misunderstandings.

Session 6. Data protection: Using the I-tool. Critical attitude towards data. Computer security. Data regulation (RGPD). Learners take a step back from all the topics covered. 30 minutes on learners' questions for the exam.
Intersession 6: Review for final exam. (Emphasis on contact with the teacher to ask questions...)

Final exam.

Sustainable Development Goals

N°9 Innovation et Infrastructures
N°12 Consommation responsable
No. 9 Innovation and infrastructure
No. 12 Responsible consumption

Number of SDG's addressed among the 17

2

Learning delivery

synchrone

Pedagogical methods

Les apprenants sont invités à beaucoup interagir durant les cours et un contact direct avec l’enseignant est disponible (e-mail / téléphone / WhatsApp / Moodle). Ils sont encouragés à poser leurs questions, à apporter leurs expériences (personnelles ou professionnelles) et à critiquer le contenu du cours. Les apprenants sont également préparés à l’examen final par des exercices donnés à la fin de chaque cours et à réaliser pour le cours suivant qui les aideront à pratiquer ce qu’il y a dans le cours en autonomie. Chaque séance est constituée d’une période de trois heures séparée en deux parties par une pause de quinze minutes. La pédagogie est dispensée par des études de cas, des travaux pratiques/dirigés, des exposés, l’utilisation de ressources en lignes (vidéos, web, applications…), des débats.

Learners are invited to interact extensively during the course, and direct contact with the teacher is available (e-mail / telephone / WhatsApp / Moodle). They are encouraged to ask questions, contribute experiences (personal or professional) and critique course content. Learners are also prepared for the final exam through exercises given at the end of each course and to be completed for the following course, which will help them to practice what is in the course independently. Each session consists of a three-hour period separated into two parts by a fifteen-minute break. Teaching methods include case studies, practical/guided work, presentations, the use of online resources (videos, web, applications, etc.) and debates.

Evaluation and grading system and catch up exams

The final exam consists of two parts. One is centered on an analysis of a topical text involving the notions seen in class, and aims to validate understanding of the cultural notions that will be exploited in business. The other is a course exercise on data management techniques, designed to assess understanding of the technologies used.
Bonus points are awarded for the completion of exercises and individual work.

In the event of failure, a make-up exam is organized, counting for 100% of the final grade (grade capped according to school regulations).

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

- Bases de données - 4e éd. Hainaut (Dunod, 2018)
- MongoDB - Comprendre et optimiser l'exploitation de vos données. Ferrandez (ENI, 2019)
- Les Blockchains. Leporcher, Goujon, Chouli (ENI, 2019)
- Mdm, Enjeux et méthodes de la gestion des données. Gabassi, Régnier-Pécastaing, Finet (Dunod, 2008)
- https://www.youtube.com/channel/UCm5wThREh298TkK8hCT9HuA
- L'enfer numérique (editionslesliensquiliberent.fr)
- Le projet Unicorn de Gene Kim (très important à lire sur la pertinence des problématiques d’entreprise et de la valeur de la donnée : livre important pour tout public / very important to read on the relevance of business issues and the value of data: an important book for any audience)

Keywords

Management, Système d’informations, Base de données, Analyses, Valeur, Modélisation / Management, Information system, Database, Analysis, Value, Modeling

Prerequisites

Aucun spécifique. Curiosité indispensable. Une connaissance générale de l’informatique et de l’entreprise est la bienvenue mais pas indispensable / No specific requirements. Curiosity essential. General knowledge of IT and business is welcome but not essential.