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BUSINESS INTELLIGENCE PROGRAMME COURSE DESCRIPTION

Code Name of the Course Unit Semester In-Class Hours (T+P) Credit ECTS Credit
YBS320 BUSINESS INTELLIGENCE 6 3 3 5

GENERAL INFORMATION

Language of Instruction : Turkish
Level of the Course Unit : BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course : Elective
Mode of Delivery of the Course Unit Face to face
Coordinator of the Course Unit Assist.Prof.Dr. HÜLYA YILMAZ
Instructor(s) of the Course Unit

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 Literature Review Data Mining 4 (techniques based on intelligent systems) Lecture & Discussion & Practice
9 - MID-TERM EXAM -
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
Mid-Term Exam 1 40 Project Midterm Report
Final Exam 1 60 Project Presentation
Practice 0 0
Short Exam 0 0
Presentation of Report 0 0
Homework Assessment 0 0
Oral Exam 0 0
Presentation of Thesis 0 0
Presentation of Document 0 0
Expert Assessment 0 0
Computer Based Presentation 0 0
TOTAL 2 100
Level of Contribution
0 1 2 3 4 5

CONTRIBUTION OF THE COURSE UNIT TO THE PROGRAMME LEARNING OUTCOMES

KNOWLEDGE

Theoretical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Define the theories, concepts and principles of the basic and sub-fields of business.
2
Explain business functions and processes based on current scientific sources.

KNOWLEDGE

Factual

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Relate internationally valid business cases with the theories and concepts of other social sciences.

SKILLS

Cognitive

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Explain the current events and facts in his / her field analytically and systematically based on advanced knowledge and skills he / she has.

SKILLS

Practical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Use the theoretical and factual knowledge in business for occupational practices.
2
Solve individual and organizational problems in business life.
3
Use computer programs (SPSS, R, Excel, Stata) efficiently against the complex business problems.

OCCUPATIONAL

Autonomy & Responsibility

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Plan research and work using knowledge and skills gained in the field of business.
2
Organize the activities for organizational goals and purposes independently.

OCCUPATIONAL

Learning to Learn

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Criticize advanced knowledge and skills in the field with a critical approach.
2
Develop the existing knowledge and skills with a critical point of view under the impact of scientific, technological and current developments.

OCCUPATIONAL

Communication & Social

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Express his/her knowledge, thoughts and solutions on business to related stakeholders in written and verbal ways.
2
Use the information and communication technology software and equipment required for business.

OCCUPATIONAL

Occupational and/or Vocational

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Apply the social, scientific, cultural and ethical values at the stages of collection of data, their implementation, interpretation and announcement of results in the field of business.
2
Relate the concepts of social rights, occupational safety, employee health, quality management and sustainability with the cases in business life.

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 42
Preliminary & Further Study 13 26
Land Surveying 0 0
Group Work 0 0
Laboratory 0 0
Reading 0 0
Assignment (Homework) 0 0
Project Work 0 0
Seminar 0 0
Internship 0 0
Technical Visit 0 0
Web Based Learning 0 0
Implementation/Application/Practice 0 0
Practice at a workplace 0 0
Occupational Activity 0 0
Social Activity 0 0
Thesis Work 0 0
Field Study 0 0
Report Writing 0 0
Final Exam 1 1
Preparation for the Final Exam 7 35
Mid-Term Exam 1 1
Preparation for the Mid-Term Exam 5 20
Short Exam 0 0
Preparation for the Short Exam 0 0
TOTAL 41 125
Total Workload of the Course Unit 125
Workload (h) / 25.5 4,9
ECTS Credits allocated for the Course Unit 5,0