COP4408 OBASE Business IntelligenceBahçeşehir UniversityDegree Programs ECONOMICSGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ECONOMICS
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
COP4408 OBASE Business Intelligence Spring 3 0 3 5
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. ADEM KARAHOCA
Course Lecturer(s): Prof. Dr. ADEM KARAHOCA
Recommended Optional Program Components: None
Course Objectives: The course provides the student with an introduction to the basic and more advanced concepts of Business Intelligence and discusses the architectures of possible solutions.

Learning Outcomes

The students who have succeeded in this course;
1. Define basic concepts and categories of business intelligence and business intelligence market
2. Describe data warehouse architectures
3. Define relational models, construct normalized data models and identify queries to data sources with SQL.
4. Discuss case studies in terms of business intelligence concepts
5. Specify data mining and clustering methods
6. Describe neural networks
7. Define decision trees
8. Identify business intelligence front end applications
9. Prepare project presentations

Course Content

Concepts of business intelligence, data warehousing, rdbms concepts, modeling the dimensions and creating the aggregations, panel - case studies, introduction to data mining unsupervised methods, supervised methods, business intelligence front end

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction to Business Intelligence
2) Data Warehousing
3) RDBMS Concepts I
4) RDBMS Concepts II
5) Modeling the Dimensions and Creating the Aggregations
6) Modeling the Dimensions and Creating the Aggregations
7) Panel - Case Study: Migros
8) Introduction to Data Mining Unsupervised Methods
9) Introduction to Data Mining Unsupervised Methods
10) Supervised Methods
11) Supervised Methods
12) Business Intelligence Front End
13) Project Presentations
14) Panel – Case Study: Turkcell

Sources

Course Notes / Textbooks: Corporate Information Factory, W. H. Inmon, Claudia Imhoff, Ryan Sousa, 2001, 0471399612

Business intelligence : a managerial approach, E. Turban, R. Sharda, J.E. Arnsson, D. King, 2007, 013234761X

The Data Warehouse Toolkit, R. Kimball, M. Ross, 1996, 0471153370
References: Yok

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance 1 % 10
Project 1 % 35
Midterms 1 % 15
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 25
PERCENTAGE OF FINAL WORK % 75
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 3 5 15
Project 1 20 20
Midterms 1 18 18
Final 1 20 20
Total Workload 115

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) As a world citizen, she is aware of global economic, political, social and ecological developments and trends. 
2) He/she is equipped to closely follow the technological progress required by global and local dynamics and to continue learning.
3) Absorbs basic economic principles and analysis methods and uses them to evaluate daily events. 
4) Uses quantitative and statistical tools to identify economic problems, analyze them, and share their findings with relevant stakeholders. 
5) Understands the decision-making stages of economic units under existing constraints and incentives, examines the interactions and possible future effects of these decisions.
6) Comprehends new ways of doing business using digital technologies. and new market structures. 
7) Takes critical approach to economic and social problems and develops analytical solutions.
8) Has the necessary mathematical equipment to produce analytical solutions and use quantitative research methods.
9) In the works he/she contributes, observes individual and social welfare together and with an ethical perspective.  
10) Deals with economic problems with an interdisciplinary approach and seeks solutions by making use of different disciplines. 
11) Generates original and innovative ideas in the works she/he contributes as part of a team.