Code | Name of the Course Unit | Semester | In-Class Hours (T+P) | Credit | ECTS Credit |
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YBS320 | BUSINESS INTELLIGENCE | 5 | 3 | 3 | 5 |
GENERAL INFORMATION |
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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 | - |
Coordinator of the Course Unit | Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ |
Instructor(s) of the Course Unit | Lecturer BEGÜM AL-Assist.Prof. MEHMET BENTÜRK |
Course Prerequisite | No |
OBJECTIVES AND CONTENTS |
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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) |
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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 |
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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 |
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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 |
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Assessment & Grading of In-Term Activities | Number of Activities | Degree of Contribution (%) | Description |
Level of Contribution | |||||
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0 | 1 | 2 | 3 | 4 | 5 |
KNOWLEDGE |
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Theoretical |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Define concepts such as management, manager and leader.
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3 | |||||
2 |
Analyze the accuracy, reliability and validity of the new information obtained from the data.
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4 |
KNOWLEDGE |
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Factual |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Report the obtained data.
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5 | |||||
2 |
Prepare software and projects related with the field.
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4 |
SKILLS |
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Cognitive |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Use the appropriate resources for data analysis related with the field.
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5 | |||||
2 |
Analyze the work processes.
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5 |
SKILLS |
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Practical |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Manage projects as part of a team.
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5 | |||||
2 |
Apply the material, techniques and analyzes in relation with the subject for project and work flows.
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5 |
OCCUPATIONAL |
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Autonomy & Responsibility |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Fulfill responsibility with a focus on result in individual and team studies.
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4 |
OCCUPATIONAL |
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Learning to Learn |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Recognizes what he/she knows about his/her field or not.
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5 | |||||
2 |
Act the theoretical knowledge in real life with learning to learn approach.
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5 | |||||
3 |
Apply different methods and techniques with an innovative approach in his/her research.
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5 |
OCCUPATIONAL |
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Communication & Social |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Apply the results obtained in accordance with voluntarism and social responsibility projects.
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5 | |||||
2 |
Establish a healthy contact with colleagues
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3 | |||||
3 |
Share the analyzes and obtained results with colleagues.
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3 | |||||
4 |
Cooperate with colleagues at international level with the help of foreign language competency.
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3 |
OCCUPATIONAL |
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Occupational and/or Vocational |
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Programme Learning Outcomes | Level of Contribution | ||||||
0 | 1 | 2 | 3 | 4 | 5 | ||
1 |
Behave in accordance with ethical values regarding the collection, analysis and reporting of data.
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5 | |||||
2 |
Participate the design of work processes and systems with full quality.
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5 | |||||
3 |
Cooperate with other employees for the continuation of sustainability in the profession.
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3 |
WORKLOAD & ECTS CREDITS OF THE COURSE UNIT |
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Workload for Learning & Teaching Activities |
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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 |
Total Workload of the Course Unit | 125 | ||
Workload (h) / 25.5 | 4,9 | ||
ECTS Credits allocated for the Course Unit | 5,0 |