COURSE UNIT TITLE

Offered By

Business Administration (English)

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR GÜZIN ÖZDAĞOĞLU

Offered to

Business Administration (English)

Course Objective

The main purpose of this course is to discuss the role of business analytics in business administration; to conduct analyses in the scope of business analytics and business intelligence for discovering the related technologies and developing the right strategies to adopt in business.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

1.Textbooks
-Business Intelligence and Analytics: Systems for Decision Support (Sharba, Delen, Turban), Pearson.
-Business Intelligence: Managerial Approach, Efraim Turban, Pearson, 2011.
-Introduction to Data Mining , Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson.
2. Software and Coding Platforms (vary based on the accessibility conditions). Possible platforms:
MS Excel
Rapidminer
R, python
Power BI

Planned Learning Activities and Teaching Methods

1) Lessons will be conducted with computer support. Students are expected to attend classes with their personal computers.

2) Theoretical sections will be supported with the relevant business cases. Basic applications will be developed by using a programming language and/or analysis environment.

3) Each student will participate in a group project, and each project will cover an business intelligence application for a business problem.

4) The group projects will also be enhanced with an AI Strategy Canvas.

5) The projects will be presented at the end of the semester

Assessment Methods

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm exam will assess the understanding level of the theoretical background of business analytics and related applications in business life.

In-semester activities will be evaluated based on the compatibility of the applications made with the approaches and technologies used in the suggested study, with business analytics and business intelligence


RUBRIC FOR EVALUATION:

1. The student is able to clearly identify the problem (by stating the reasons, conditions,etc) (5 pts)
2. The student is able to identify research questions (5 pts).
3. The student is able to collect or extract relevant qualitative and/or quantitative data (10 pts).
4. The student is able to apply exploratory data analysis with proper visuals for summarizing your dataset, such as tables, graphs, dashboards (10 pts).
5. The student is able to discover the relevant preprocessing and apply them on the dataset (15 pts).
6. The student is able to select techniques and algorithms to complete the data model aligned with the research questions (give the details of the algorithms with the related literature) (10 pts).
7. The student is able to analyze the selected model using appropriate tools and technologies (Power Bi, Python or R IDEs, RapidMiner etc) (15 pts).
8. The student is able to select and use the appropriate indicators to measure the performance of the model (10 pts).
9. The student is able to explain the performance of your model and discuss its quality for future use (10 pts).
10. The student is able to explain the main findings with their practical implications (10pts).

Language of Instruction

English

Course Policies and Rules

Plagiarism will result in disciplinary action.
It is compulsory to attend at least 70 % of the face-to-face courses and strongly recommended for online courses.
Assignments will not be accepted unless submitted on time.

Contact Details for the Lecturer(s)

guzin.kavrukkoca@deu.edu.tr

Office Hours

TBA

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes