MECHATRONICS 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	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 Mechatronics Engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2)	Identify, formulate, and solve complex Mechatronics Engineering problems; select and apply proper modeling and analysis methods for this purpose.
3)	Design complex Mechatronic systems, processes, devices or products under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose.
4)	Devise, select, and use modern techniques and tools needed for solving complex problems in Mechatronics Engineering practice; employ information technologies effectively.
5)	Design and conduct numerical or pysical experiments, collect data, analyze and interpret results for investigating the complex problems specific to Mechatronics Engineering.
6)	Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Mechatronics-related problems.
7)	Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. Write and understand reports, prepare design and production reports, deliver effective presentations, give and receive clear and understandable instructions.
8)	Recognize the need for life-long learning; show ability to access information, to follow developments in science and technology, and to continuously educate oneself.
9)	Develop an awareness of professional and ethical responsibility, and behave accordingly. Be informed about the standards used in Mechatronics Engineering applications.
10)	Learn about business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.
11)	Acquire knowledge about the effects of practices of Mechatronics Engineering on health, environment, security in universal and social scope, and the contemporary problems of Mechatronics engineering; is aware of the legal consequences of Mechatronics engineering solutions.