ELECTRICAL AND ELECTRONICS ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
COP4408 | OBASE Business Intelligence | Spring Fall |
3 | 0 | 3 | 5 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
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. |
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 |
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 |
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 |
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 |
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 |
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 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Adequate knowledge in mathematics, science and electric-electronic engineering subjects; ability to use theoretical and applied information in these areas to model and solve engineering problems. | |
2) | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | |
3) | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.) | |
4) | Ability to devise, select, and use modern techniques and tools needed for electrical-electronic engineering practice; ability to employ information technologies effectively. | |
5) | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems. | |
6) | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | |
7) | Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. | |
8) | Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | |
9) | Awareness of professional and ethical responsibility. | |
10) | Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development. | |
11) | Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions. |