Business Intelligence, Knowledge Management and Data Mining

Crédit : 3 ECTS
Langue du cours : anglais

Volume horaire

  • CM : 21 h

Compétences à acquérir

Upon successful completion of the course, the student will :
  • Apprehend the challenges of data mining, business intelligence and knowledge management
  • Be familiarized with knowledge management, knowledge management projects
  • Understand the value added of business analytics

Description du contenu de l'enseignement

Business intelligence, data mining and knowledge management are three related and ever-present notions in any business, organization, newspapers or annual reports. In the so-called “society of knowledge”, competitive advantage stems from acquiring, managing and supporting knowledge and its related processes: learning and data mining. Being able to analyze any data and information, to learn from its environment is currently seen as a source of competitiveness. In this context, it seems necessary for any manager or leader to master those notions. This course aims at giving an overview of those concepts: business intelligence, data mining and knowledge management. This class seeks to join both academic and professional approaches through two lecturers with different backgrounds and diverse methodological approaches: lecture, case study, experience sharing and role-play.
Current management cannot rely only on feeling and intuition, though managers need data: statistics, graphs, data mining, optimizations, etc. Data Mining is, according to the Massachusetts Institute of Technology, one of the ten technologies with will change the 21° century world. Future manager will for sure need business intelligence.

Planning course :
  • Session 1 - Introduction to KM – Challenges and reality in organizations
  • Session 2 - Role play
  • Session 3 - Danone case
  • Session 5 - Business Intelligence. Overview and positioning. Market Trends and the critical role of BI
  • Session 6 - BI for CRM, Risk, Performance. Management. Data Mining. Future of BI.
  • Session 7 - Case study to be determined

Mode de contrôle des connaissances

  • Role play : 50%
  • Working paper : 50%

In the academic area, a working paper is a text providing an overview of a precise topic with relevant references of previous works, and including some personal proposals of the author. Topics will be defined in class. We expect you to use creativity, research, what you learned and (as much as possible) past experience to propose a complete answer. We praise quality over quantity. As indication we estimate that a comprehensive but concise working paper should be limited to 10 pages. This has to be a professional document: structure and readability are important, be as concise and concrete as possible. We don’t tolerate for a copy and paste of an existing marketing flyer for BI. Research is as important as creativity/your own opinion. You may want to illustrate your propositions/statements as much as you can with concrete examples.

Bibliographie, lectures recommandées

Recommended books :
  • “Learning to Fly: Practical Knowledge Management from Leading and Learning Organizations » by Chris Collison, Geoff Parcel, 2005.
  • “Competing on Analytics”, Davenport & Harris (2007) Publisher: Harvard Business School Press.
  • “Manager’s Guide to Making Decisions about Information Systems”, Paul Gray (2006), Publisher: John Wiley & Sons, Inc, format: 326 pp.

Enseignant responsable

CHARLOTTE FILLOL

Enseignant responsable

GRÉGOIRE DE LASSENCE



Année universitaire 2016 - 2017 - Fiche modifiée le : 13-02-2017 (15H32) - Sous réserve de modification.