Basics of Business Data(G317)
| Course Code | Course Name | Semester | Theory | Practice | Lab | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| G317 | Basics of Business Data | 5 | 3 | 0 | 0 | 3 | 5 |
| Prerequisites | |
| Admission Requirements |
| Language of Instruction | English |
| Course Type | Elective |
| Course Level | Bachelor Degree |
| Course Instructor(s) | Deniz UZTÜRK BARAN uzturkdeniz@gmail.com (Email) |
| Assistant | |
| Objective | The aim of this course is to introduce students to the fundamental concepts and applications of business data in organizational decision-making processes. It provides a foundational understanding of data collection, storage, cleaning, analysis, and interpretation, with a strong emphasis on ethical considerations and real-world applications. The course also aims to develop students’ data literacy and analytical thinking skills, equipping them to approach data-driven problems in modern business environments with confidence. |
| Content |
Week 1 Introduction to Business Data and Analytics (1) Week 2 Introduction to Business Data and Analytics (2) and Presentation of Semester-Beginning Assignments Week 3 Data Fundamentals in Business Week 4 Data Collection Methods and Applications Review Week 5 Data Storage Solutions and Applications Review Week 6 Data Cleaning and Preparation (1) Week 7 Data Cleaning and Preparation (2) Week 8 MIDTERM EXAM (Final Project Topics will be provided) Week 9 Introduction to Data Analysis (1) Week 10 Introduction to Data Analysis (2) and Excel Applications Week 11 Data Mining Techniques Week 12 Ethics in Data Analytics Week 13 Implementation of Data-Driven Solutions and Case Studies Week 14 Course Wrap-Up and Final Project Presentations |
| Course Learning Outcomes |
Upon successful completion of this course, students will be able to: 1. Explain the role and importance of business data in decision-making and strategy development. 2. Identify and compare different data collection methods and evaluate their applicability in business contexts. 3. Understand and apply basic data storage and data management techniques. 4. Perform data cleaning and preparation procedures to ensure data quality and usability. 5. Demonstrate the ability to conduct basic data analysis using descriptive techniques and Excel-based tools. 6. Recognize common data mining techniques and describe their relevance to business challenges. 7. Evaluate ethical and legal considerations in data analytics, including data privacy and responsible data use. 8. Develop and present data-driven solutions through structured projects and case studies. |
| Teaching and Learning Methods | The course is taught through interactive lectures, in-class discussions, hands-on exercises, and group presentations. Teaching methods include theoretical instruction, practical applications using Excel, and case-based learning. Students are actively engaged in project-based tasks such as poster presentations, midterm evaluations, and final project work that simulates real-world data analysis problems. Throughout the course, emphasis is placed on both the technical and ethical dimensions of handling business data. |
| References |
- Camm, J. D., Cochran, J. J., Fry, M. J., & Ohlmann, J. W. (2024). Business analytics: Descriptive, predictive, prescriptive. Cengage Learning. - Provost, Foster, and Tom Fawcett. Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking. O'Reilly Media, 2013. - Mayer-Schönberger, Viktor, and Kenneth Cukier. Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt, 2013. Readings and case studies will be provided throughout the course. The beginning and end-of-semester assignments are mandatory and must be completed to pass the course. |
Theory Topics
| Week | Weekly Contents |
|---|
Practice Topics
| Week | Weekly Contents |
|---|
Contribution to Overall Grade
| Number | Contribution | |
|---|---|---|
| Contribution of in-term studies to overall grade | 3 | 60 |
| Contribution of final exam to overall grade | 1 | 40 |
| Toplam | 4 | 100 |
In-Term Studies
| Number | Contribution | |
|---|---|---|
| Assignments | 1 | 10 |
| Presentation | 1 | 20 |
| Midterm Examinations (including preparation) | 1 | 30 |
| Project | 0 | 0 |
| Laboratory | 0 | 0 |
| Other Applications | 0 | 0 |
| Quiz | 0 | 0 |
| Term Paper/ Project | 0 | 0 |
| Portfolio Study | 0 | 0 |
| Reports | 0 | 0 |
| Learning Diary | 0 | 0 |
| Thesis/ Project | 0 | 0 |
| Seminar | 0 | 0 |
| Other | 0 | 0 |
| Make-up | 0 | 0 |
| Toplam | 3 | 60 |
| No | Program Learning Outcomes | Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | The acquisition of high-level knowledge of the functions of production management and marketing, management, accounting and finance; the skill of using this knowledge. | X | ||||
| 2 | The acquisition of basic conceptual knowledge about scientific fields related to professional life, such as law, economics, sociology, psychology, social psychology and quantitative methods. | X | ||||
| 3 | The ability to work effectively in a team; the ability to pass on knowledge to other members of the team. | X | ||||
| 4 | The competence to use his/her knowledge on the field, to analyze and interpret the data obtained, to identify the problems encountered, to provide appropriate solutions and scientifically defend these solution suggestions when necessary. | X | ||||
| 5 | The competence to determine the aims and objectives of the company or institution in which he/she is employed by taking into account the needs, the competitive dynamics of the market and by calculating the risks incurred; the ability to engage in entrepreneurship and establish and manage a business. | X | ||||
| 6 | Awareness of constantly updating his/her professional knowledge and skills; the ability to adapt to change and innovation; the competence to evaluate critically the information he/she has acquired. | X | ||||
| 7 | Basic knowledge of information and communication technologies required for professional life; the ability to use core office programs at an advanced level; expertise in data processing and report writing in the IT environment. | X | ||||
| 8 | Ability to follow current information in his/her field in both English and French and to communicate in writing and verbally with stakeholders in both languages. | X | ||||
| 9 | The ability to conduct researches and studies taking into account the market, dynamics of competition, organizational and global factors and scientific methods; contribute to projects, take responsibility in projects, display competence to make innovative and effective decisions. | X | ||||
| 10 | Ability to develop strategies, find creative solutions to management problems by building relations with other areas of the social sciences and take the responsibility of these decisions. | X | ||||
| 11 | Consciousness of taking into account ethical values, when making decisions and being involved in business life. | X | ||||
| 12 | Awareness of the impact of practices related to his/her field on the global and social dimensions (universality of social rights, social justice, cultural values, environmental problems, sustainability, etc.) and their legal consequences. | X | ||||
| Activities | Number | Period | Total Workload |
|---|---|---|---|
| Class Hours | 14 | 3 | 42 |
| Working Hours out of Class | 12 | 3 | 36 |
| Assignments | 1 | 2 | 2 |
| Presentation | 1 | 14 | 14 |
| Midterm Examinations (including preparation) | 1 | 8 | 8 |
| Project | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Other Applications | 0 | 0 | 0 |
| Final Examinations (including preparation) | 1 | 14 | 14 |
| Quiz | 0 | 0 | 0 |
| Term Paper/ Project | 0 | 0 | 0 |
| Portfolio Study | 0 | 0 | 0 |
| Reports | 0 | 0 | 0 |
| Learning Diary | 0 | 0 | 0 |
| Thesis/ Project | 0 | 0 | 0 |
| Seminar | 0 | 0 | 0 |
| Other | 0 | 0 | 0 |
| Make-up | 0 | 0 | 0 |
| Total Workload | 116 | ||
| Total Workload / 25 | 4.64 | ||
| Credits ECTS | 5 | ||