Department of Information and Computing Sciences

Departement Informatica Onderwijs
Bachelor Informatica Informatiekunde Kunstmatige intelligentie Master Computing Science Game&Media Technology Artifical Intelligence Business Informatics

Onderwijs Informatica en Informatiekunde

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Business intelligence

Website:website containing additional information
Course code:INFOMBIN
Credits:7.5 ECTS
Period:period 3 (week 6 through 16, i.e., 4-2-2013 through 19-4-2013; retake week 22)
Timeslot:B
Participants:up till now 36 subscriptions
Schedule:Official schedule representation can be found in Osiris
Teachers:Dit is een oud rooster!
formgrouptimeweekroomteacher
lecture          Marco Spruit
 
tutorial          Michiel Meulendijk
Simon Rosman
  
Exam:
week: 26Thu 28-6-201817.00-20.00 uurroom: EDUC-THEATRON
week: 28Thu 12-7-201813.30-16.30 uurroom: EDUC-ALFAretake exam
Contents:

This course deals with a collection of computer technologies that support managerial decision making by providing information of both internal and external aspects of operations. They have had a profound impact on corporate strategy, performance, and competitiveness, and are collectively known as business intelligence.

This course has been designed with the following learning objectives in mind:
  • Understand the fundamentals of the collection of technologies called Business Intelligence (BI)
  • Understand the relationships between BI technologies within a typical BI architecture
  • Relate the theoretical foundations to professional experiences in daily practice
  • Experience the typical steps performed in a BI implementation project
  • Obtain hands-on experience with professional BI tooling
  • Understand current state-of-the-art research in BI technologies
During this course the following BI topics will be covered:
  • Business perspective
  • Statistics
  • Data management
  • Data integration
  • Data warehousing
  • Data mining
  • Reporting and online analytic processing (i.e., descriptive analytics)
  • Quantitative analysis and operations research (i.e., predictive analytics)
  • Management communications (written and oral)
  • Systems analysis and design
  • Software development
Literature:The lectures will be centered around the well-known book which you need to have in your possession before lecture 1:

This course book has the following structure:

  1. Introduction to Business Intelligence
  2. Data Warehousing
  3. Business Performance Management
  4. Data Mining for Business Intelligence
  5. Text and Web Mining
  6. Business Intelligence Implementation: Integration and Emerging Trends
Also, a number of scientific papers will be part of the study materials.
These are listed on the Course website's Materials Download page (only accessible by course students).
Course form:In general, the following course setup will be executed:
  • Tue 9:00-10.45 - Guest lectures on illustrations from business practice.
  • Tue 11:00-12.45 - Workshops in computer room where you will work on the BI team project. Also, project milestone team presentations will occasionally be held.
  • Thu 13:15-15.00 - Regular lectures based on THE BOOK.
However, the lecture slots may be switched according to guest availability. Also, we will have a crash course BI using Jedox on Tuesday 5 February (intro) and Thursday February 7 from 13:15-15:00 in BBL-079 AND 15:15-17:00 in BBL-075.
Exam form:Balancing out theory, practice and participation on BI is also reflected in the course grading balance:
  • Exam: 1 written exam, with one 2nd chance exam opportunity.
  • Project: 1 BI team project grade, consisting of the final project deliverable.
  • Talks: Most notably, scientific paper analysis talk, but also including project milestone and other presentations.
Final grade: (0.4 * Exam) + (0.4 * Project) + (0.2 * Talks+Participation)
Minimum effort to qualify for 2nd chance exam:You need to have:
  • attended the BI crash course.
  • attended at least 80% of the guest lectures.
  • attended at least 80% of the workshops.
  • co-presented at least one journal paper analysis.
  • co-presented at least 50% of the milestone presentations.
Description:Please refer to the MBIN course website for more info.
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