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 : |
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. ÇAĞLA TUĞBERK ARIKER |
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 |
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 the 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 |
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 |
|