Business intelligence
- UE code EDASM101
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Schedule
45 15Quarter 2
- ECTS Credits 5
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Language
Français
- Teacher Linden Isabelle
At the end of this course, students will be able to define the main concepts of BI, discuss their integration into performance management and study the impact of a BI system at different levels of an organisation. They will be able to summarise the models useful for the different stages of development of a BI platform and to carry out an implementation in standard tools based on the studied methodology.
Every organisation is full of data in electronic form. Is it capable of extracting useful information from it? This course presents the main tools proposed by Business Intelligence, their architecture and their implementation. It then examines how they can contribute to performance management and support decision making at both strategic and operational levels. In particular, the course covers: • BI vs ERP • Classical architecture of a BI pollution • ETL and Data • Multi-dimensional models and OLAP • Data Warehouse Modeling • Data Warehouse architecture • BI and Data Mining • KPI, Dashboard, Scorecards and Cockpit • Real-time BI
The assessment is based on the development of a platform in a group work and on an oral examination. The group work is evaluated on the basis of the following criteria • interim implementation reports and documentation through templates • an oral presentation of the platform. Given the collective and follow-up arrangements, the work is assessed in a single session and the score obtained is valid for both sessions. The oral examination is only open to students who have presented the work (Article 38 of the EAR). Details of the assessment and the various assignments as well as the submission dates are given in the first course and on the webcampus
• Business Intelligence, First European Summer School, eBISS 2011, Paris, France, July 2011, Tutorial Lectures, MarieAude Aufaure, Esteban Zimanyi (Eds), LNBIP 96, Springer. • Business Intelligence, Second European Summer School, eBISS 2012 Brussels, Belgium, July 2012, Tutorial Lectures, Marie-Aude Aufaure, Esteban Zimanyi (Eds), LNBIP 138, Springer. • The Balanced Scorecard, Kaplan & Norton • Performance Dashboards, Wayne Eckerson • Key Performance Indicator, David Parmenter • The BI roadmap, Moss & Atre • Succesful BI, Cindy Howson • Data Warehouse, Kimball • News on websites: • Gartner: http://www.gartner.com/ • Forester: http://www.forrester.com/ • The data warehousing institute: www.tdwi.org • http://www.teradatauniversitynetwork.com/tun/
Training | Study programme | Block | Credits | Mandatory |
---|---|---|---|---|
Master 120 en sciences mathématiques, à finalité spécialisée en data science | Standard | 0 | 5 | |
Certificat d'université d'Executive Master en Data Science | Standard | 0 | 5 | |
Master 120 en sciences informatiques, à finalité spécialisée en data science | Standard | 0 | 5 | |
Master 120 en ingénieur de gestion, à finalité spécialisée en data science | Standard | 0 | 5 | |
Certificat d'université d'Executive Master en Data Science | Standard | 1 | 5 | |
Master 120 en sciences informatiques, à finalité spécialisée en data science | Standard | 1 | 5 | |
Master 120 en ingénieur de gestion, à finalité spécialisée en data science | Standard | 1 | 5 | |
Master 120 en sciences mathématiques, à finalité spécialisée en data science | Standard | 2 | 5 |