İzmir Ekonomi Üniversitesi
  • TÜRKÇE

  • GRADUATE SCHOOL

    Master of Business Administration - Distance Learning (e-MBA) (Turkish)

    EISL 518 | Course Introduction and Application Information

    Course Name
    Data Analytics for Business
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    EISL 518
    Fall/Spring
    3
    0
    3
    5

    Prerequisites
    None
    Course Language
    Turkish
    Course Type
    Elective
    Course Level
    Second Cycle
    Mode of Delivery Online
    Teaching Methods and Techniques of the Course Group Work
    Problem Solving
    Case Study
    Lecture / Presentation
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s)
    Assistant(s) -
    Course Objectives The course aims to show the usefulness of data-driven approach in business life. Its goal is to teach essential data science knowledge, tools, and practice in the analysis of business problems.
    Learning Outcomes

    The students who succeeded in this course;

    • Students who successfully complete the course will be able to; Apply the data analytics approaches to different business functional areas, e.g., marketing, finance, production, and human resources.
    • Choose an appropriate analytical method according to the type of business problem.
    • Analyze business problems with alternative analytical tools.
    • Interpret the outputs of data analysis applied on business problems.
    • Develop programming skills for data analysis
    Course Description This course shows how to exploit data analytics in business problems. It teaches the application of data analytic techniques on business problems via an open source programming language.

     



    Course Category

    Core Courses
    Major Area Courses
    X
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Introduction to Business Analytics and R Chapters 2 & 3 (p. 30-80). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları. Nobel Akademik Yayıncılık. ISBN: 978-625-417-474-2
    2 Creating Data Sets for Business Problems Chapter 4 (p. 84-120). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları
    3 Making Data Ready for Business Analysis Chapter 4 (p. 84-120). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları
    4 Making Data Ready for Business Analysis Chapters 10 & 11 (p. 177-191). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu. Pusula. ISBN: 6056460894
    5 Gaining Insights on Business Problems by Visualizing Data Chapter 14 (p. 249-308). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu
    6 Gaining Insights on Business Problems by Visualizing Data Chapter 14 (p. 249-308). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu
    7 Basic Statistics
    8 Sales Data Analysis with Multiple Linear Regression Chapter 16 (p. 339-357). Arslan İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu
    9 Financial Risk Analysis with Multiple Logistic Linear Regression Chapter 13 (p. 379-386). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları
    10 Product Defect Risk Analysis with Decision Trees Chapter 11 (p. 284-313). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları
    11 Customer Segmentation Chapter 8 (p. 208-232). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları
    12 Text Analysis on Customer Reviews Chapter 17 (p. 460-491). Hızıroğlu vd. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları
    13 Homework Presentations
    14 Homework Presentations
    15 Semester Review
    16 Final Exam

     

    Course Notes/Textbooks

    Hızıroğlu, A., Cebeci, H.İ., Codal K.Ç. (2022). Veri Modelleme ve Veri Analitiği - Sağlık ve İşletme Uygulamaları. Nobel Akademik Yayıncılık. ISBN: 978-625-417-474-2

     

    Arslan, İ. (2015). R İle İstatistiksel Programlama Veri Analitiği İçin Yeni Bir Yazılım Platformu. Pusula. ISBN-10: 6056460894

    Suggested Readings/Materials

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing
    Participation
    1
    5
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    1
    15
    Presentation / Jury
    Project
    Seminar / Workshop
    Oral Exams
    Midterm
    Final Exam
    1
    80
    Total

    Weighting of Semester Activities on the Final Grade
    2
    20
    Weighting of End-of-Semester Activities on the Final Grade
    1
    80
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    14
    2
    28
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    1
    34
    34
    Presentation / Jury
    0
    Project
    0
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    0
    Final Exam
    1
    40
    40
        Total
    150

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1

    To be able to demonstrate general business knowledge and skills.

    -
    -
    X
    -
    -
    2

    To be able to demonstrate business communication skills effectively.

    -
    -
    -
    -
    -
    3

    To be able to deliver creative and innovative solutions to the business-related problems.

    -
    -
    -
    -
    -
    4

    To be able to evaluate the performance of business organizations through a holistic approach.

    -
    -
    -
    -
    -
    5

    To be able to take a critical perspective in evaluating business knowledge.

    -
    -
    -
    -
    -
    6

    To be able to exhibit an ethical and socially responsible behavior in conducting research and making business decisions.

    -
    -
    -
    -
    -
    7

    To be able to solve business related problems using analytical and technological tools and techniques.

    -
    -
    -
    -
    X
    8

    To develop a solution to business problems through systematic research.

    -
    -
    X
    -
    -
    9

    To be able to use a foreign language to follow information about the field of business and participate in discussions in academic environments.

    -
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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