COP4408 OBASE Business IntelligenceBahçeşehir UniversityDegree Programs INDUSTRIAL ENGINEERINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
INDUSTRIAL ENGINEERING
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 Fall
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) Build up a body of knowledge in mathematics, science and industrial engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2) Identify, formulate, and solve complex engineering problems; select and apply proper analysis and modeling methods for this purpose.
3) Design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose. The ability to apply modern design methods to meet this objective.
4) Devise, select, and use modern techniques and tools needed for solving complex problems in industrial engineering practice; employ information technologies effectively.
5) Design and conduct experiments, collect data, analyze and interpret results for investigating the complex problems specific to industrial engineering.
6) Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working independently.
7) Demonstrate effective communication skills in both oral and written English and Turkish. Writing and understanding reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instructions.
8) Recognize the need for lifelong learning; show ability to access information, to follow developments in science and technology, and to continuously educate him/herself.
9) Develop an awareness of professional and ethical responsibility, and behaving accordingly. Information about the standards used in engineering applications.
10) Know business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.
11) Know contemporary issues and the global and societal effects of modern age engineering practices on health, environment, and safety; recognize the legal consequences of engineering solutions.
12) Develop effective and efficient managerial skills.