Business Intelligence and Analytics

2018-2019

Course Objective

Quantitative Skills
•Using business intelligence and data mining suites to create insight
from data and tackle business problems

Knowledge
•Defining, describing and recalling the basic concepts, constituent
components, principles and theories underlying the use and the
deployment of business intelligence & analytics solutions.

Bridging Theory and Practice
•Choosing, applying, and evaluating business intelligence & analytics
concepts, principles and solutions to solve business problems.

Course Content

Dealing with the overabundance of data and the ability to transform data
into insights have become critical success factors for organizations.
This course offers the handles that are needed to unleash the potential
of data, and business intelligence and analytics solutions in order to
create competitive advantage. The course primarily has a managerial
focus. The students will acquire hands-on experience with trending BI&A
technologies to learn how to use their features and characteristics in
practice. Our partners from the industry and the business consulting
sector will be closely involved in the course, sharing their insights
and experience during several interventions.

Keywords in this area are ‘big data’, ‘data science’, ‘business
intelligence’, ‘data mining’ and ‘data-driven decision making and
innovations’.

Teaching Methods

Lectures
Tutorials
Workshops

Method of Assessment

Assessment Written exam – Individual assessment
Interim Assignment(s) / Tests:
Analytics practicum tests – Individual assessment

Literature

This course is article based.
Readings will be announced in the course manual.

Recommended background knowledge

Recommended knowledge Elementary course on (Management) Information
Systems (for example: Laudon, K.C. & Laudon, J.P. (2016). Essentials of
MIS (12 th edition).
Knowledge of the fundamentals of statistics.

Course Introduction to Digital Innovation (SBE, Period 3.1).
BK: 2.1 Business Information Technology
IBA: 2.1 Business Information Systems

General Information

Course Code E_MM_BIA
Credits 6 EC
Period P2
Course Level 300
Language of Tuition English
Faculty School of Business and Economics
Course Coordinator M. Shafeie Zargar
Examiner M. Shafeie Zargar
Teaching Staff dr. A.C. Smit
M. Shafeie Zargar
dr. M.G.A. Plomp

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar, Lecture, Response class
Target audiences

This course is also available as: