COMPUTER 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 | 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 computer engineering; the ability to use theoretical and practical knowledge in these areas in complex engineering problems. | |
2) | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | 2 |
3) | Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. | 3 |
4) | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; ability to use information technologies effectively. | |
5) | Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or computer engineering research topics. | 3 |
6) | Ability to work effectively within and multi-disciplinary teams; individual study skills. | 2 |
7) | Ability to communicate effectively in verbal and written Turkish; knowledge of at least one foreign language; ability to write active reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |
8) | Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew continuously. | |
9) | To act in accordance with ethical principles, professional and ethical responsibility; information on the standards used in engineering applications. | |
10) | Information on business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; information about sustainable development. | |
11) | Knowledge of the effects of engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in engineering; awareness of the legal consequences of engineering solutions. |