Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
1BIA 502Veri Odaklı İşletme Yönetimi3+0+038

Course Details
Language of Instruction Turkish
Level of Course Unit Master's Degree
Department / Program MA Program in Big Data and Business Analytics (Thesis) (Turkish)
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course In the data-driven business management course, it is aimed to provide basic information about the use of various information technologies and data analytics techniques during the identification, development and implementation of opportunities that arise in the business process. For this purpose, methods are given to ensure that the management processes in the planning, organizing, directing, coordinating and supervising steps, which are the basic elements of a business management, are based on data. Managers use this data to integrate activities and processes in the work area and to increase efficiency.
Course Content In the process that starts with data structures and obtaining data in the business, studies are carried out to extract the useful part from the data by using techniques such as data classification and time analysis. Forecasting using these With the help of algorithms, it is decided which position/measures the business will take based on future probabilities.
Course Methods and Techniques There will be interactive presentations and case studies.
Prerequisites and co-requisities None
Course Coordinator Prof.Dr. Ümit Hacıoğlu
Asist Prof.Dr. Merve Şahin
Name of Lecturers Asist Prof.Dr. Taner Ayaz
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Articles
Case Studies
Muhteşem Baran (2017) Büyük Veri, Bilgi Yönetimi ve İş Zekası, Beta Yayınevi
Ünal Yarımağan (2022) Veri Tabanı Sistemleri, Seçkin Kitabevi
canvas.ihu.edu.tr
canvas.ihu.edu.tr

Course Category
Mathematics and Basic Sciences %10
Engineering %5
Engineering Design %5
Social Sciences %40
Field %40

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Assignment 2 % 40
Final examination 1 % 60
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 5 70
Assignments 2 30 60
Final examination 1 60 60
Total Work Load   Number of ECTS Credits 8 232

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Define data structures
2 Outline the basic management processes in businesses
3 Describe the necessary steps for collecting data in enterprises and identify abnormal ones
4 Analyze marketing, customer and employee data
5 Define forecasting algorithms and apply them
6 List the necessary conditions for obtaining data in accordance with ethical and legal rules


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 What is data and how can the DKIW pyramid be applied in business?
2 Data sources in businesses
3 Collecting data and sorting out erroneous/incomplete data
4 Business processes and making sense of data accordingly
5 Methods of data analysis
6 BPM and process modeling techniques
7 Use of data in optimizing business processes
9 Analysis of marketing data
10 Use of data in customer segmentation
11 Analysis of employee data
12 Analysis of financial data
13 Ethics in data use
14 Presentations


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7
C1 3 4 2 3 3 2
C2 2 3 3 4
C3 4 5 2 4 3 3
C4 4 4
C5 4 3 2 5 4 3
C6 3 3 5

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant


https://obs.ihu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=210843&lang=en