BUSINESS INTELLIGENCE PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
YBS320	BUSINESS INTELLIGENCE	5	3	3	5

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	, TYY: + , EQF-LLL: , QF-EHEA:
Type of the Course :	Elective
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit
Instructor(s) of the Course Unit
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	This course aims to introduce the latest developments in the world about big data concept and business intelligence applications, and to provide students with the necessary analysis skills.
Contents of the Course Unit:	Contents of the course include the subjects such as Business Intelligence, Data Mining, Web Mining, Text Mining, Business Intelligence Applications.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Know the appropriate methods of the business process for developing business intelligence.
Relate between business performance management and business intelligence.
Experiment web and text mining tools.
Apply the rules of association in business intelligence processes.
Design business processes with classification and clustering knowledge and skills.
Choose the appropriate methods for data reduction.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	-	Introduction to Business Intelligence	Lecture & Discussion & Practice
2	Literature Review	Business intelligence and decision support systems / intelligent systems	Lecture & Discussion & Practice
3	Literature Review	Data warehouse and special database	Lecture & Discussion & Practice
4	Literature Review	Data Visualization and Reporting	Lecture & Discussion & Practice
5	Literature Review	Data Mining 1 (basic concept and process)	Lecture & Discussion & Practice
6	Literature Review	Data Mining 2 (statistics based techniques)	Lecture & Discussion & Practice
7	Literature Review	Data Mining 3 (techniques based on machine)	Lecture & Discussion & Practice
8	-	MID-TERM EXAM	-
9	Literature Review	Data Mining 4 (techniques based on intelligent systems)	Lecture & Discussion & Practice
10	Literature Review	Text Mining	Lecture & Discussion & Practice
11	Literature Review	Web Mining	Lecture & Discussion & Practice
12	Literature Review	Data Mining Practices	Lecture & Discussion & Practice
13	Literature Review	Business Performance Management	Lecture & Discussion & Practice
14	Literature Review	Developing and practicing in Business Intelligence process	Lecture & Discussion & Practice
15	Literature Review	Business Intelligence Practices	Lecture & Discussion & Practice
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Cagiltay, N. E. (2010). Is zekasi ve veri ambari sistemleri. ODTU Gelistirme Vakfi Publications.
Seker, S. E. (2013). Is zekasi ve veri madenciligi Cinius Publications.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Describe basic theories of microeconomics and macroeconomics by benefiting from assumptions and axioms.
2	Recognize the entries in the book and financial balance sheet of the business organization.
3	Define concepts, theories and principles of basic and subfields of international trade by adhering to the background knowledge.

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Summarize historical development of the international trade theories by adhering to the chronological order.
2	Use theoretical knowledge gained in the field of international trade in occupational practices and daily life.
3	Solve financial and legal problems confronted in international trade practices.

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Relate statistical raw data by benefiting from computer programs and relate data with one another in consideration of theoretical knowledge.
2	Evaluate developments in the world in consideration of common courses in the faculty with an intellectual perspective.

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Interpret current events and facts in international trade based on advanced knowledge and skills from an analytical and systematic holistic view.

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Relate knowledge about economic globalization and internationalization with current knowledge in the field.

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Examine current economic policies applied over the gained advanced knowledge and skills by a critical approach.

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Explain demands in written or verbally by using the foreign language skill in business and social life effectively.
2	Tell knowledge, thoughts and solution offers regarding subjects in international trade to relevant stakeholders demands in written or verbally.
3	Design a healthy communication network for themselves in the business world by using social life skills.

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Analyze current issues, events and problems by benefiting from theoretical and historical knowledge of international trade and economics.
2	Develop suggestions for international trade policies by determining economic problems in the macro level.
3	Apply commercial applications in consideration of knowledge gained in financing and management of international trade by being inclusive of international market
4	Discuss the effects of commercial and financial globalization processes on the income distribution, by benefiting from data.

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	13	2	26
Land Surveying	0	0	0
Group Work	0	0	0
Laboratory	0	0	0
Reading	0	0	0
Assignment (Homework)	0	0	0
Project Work	0	0	0
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	0	0	0
Final Exam	1	1	1
Preparation for the Final Exam	7	5	35
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	5	4	20
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	41	0	125