School/Faculty/Institute Faculty of Economics, Administrative and Social Sciences
Course Code MGMT 431
Course Title in English Business Intelligence
Course Title in Turkish İş Zekası
Language of Instruction EN
Type of Course Select
Level of Course Select
Semester Fall
Contact Hours per Week
Lecture: 3 Recitation: Lab: Other:
Estimated Student Workload 124 hours per semester
Number of Credits 5 ECTS
Grading Mode Standard Letter Grade
Pre-requisites MIS 301 - Management Information Systems
Expected Prior Knowledge None
Co-requisites None
Registration Restrictions Only Undergraduate Students
Overall Educational Objective To understand and query sql command for business/marketing professionals and the structure of Business Intelligence projects and development of main layer.
Course Description In business world, it is expected that all employees will be analytical enough to their needs and add value to their companies. Business Administration department graduates are expected to communicate with technical departments, adopt a data-driven company culture and improve themselves in the data analytics to be aware of the added value they can create. The aim of this course is to make the students more adaptable to the business analytics world by explaining the concept of purposeful business intelligence, successful/unsuccessful examples in real life, benefits of analytical layers to companies, layers of business intelligence projects and data visualization.
Course Description in Turkish İş dünyasında, ihtiyaçlar doğrultusunda tüm çalışanların yeterli düzeyde analitik olmaları ve şirketlerine değer katmaları beklenmektedir. İşletme bölümü mezunlarının teknik departmanlarla iletişim kurmaları, veri odaklı bir şirket kültürü benimsemeleri ve oluşturabilecekleri katma değerin farkında olmak için veri analizinde kendilerini geliştirmeleri beklenmektedir. Bu dersin amacı öğrencilere amaca yönelik iş zekası, gerçek hayatta başarılı/başarısız örnekler, analitik katmanların şirketlere faydaları, iş zekası projeleri katmanları ve veri görselleştirme kavramlarını açıklayarak iş analitiği dünyasına daha uyumlu hale getirmektir.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) do simple query on tables using SQL commands
2) understand of operational data layer
3) understand of analytical data layer
4) design to Business Intelligence project
5) visualize data.
Program Learning Outcomes/Course Learning Outcomes 1 2 3 4 5
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.
6) Internalization and dissemination of professional ethical standards.
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity.
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.
12) Ability to acquire knowledge independently, and to plan one’s own learning.
13) Demonstration of advanced competence in the clarity and composition of written work and presentations.

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. N
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. N
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. H Exam,HW,Participation
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. N
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. N
6) Internalization and dissemination of professional ethical standards. N
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. N
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). N
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. S Participation
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. S HW,Participation
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. N
12) Ability to acquire knowledge independently, and to plan one’s own learning. S Exam,HW
13) Demonstration of advanced competence in the clarity and composition of written work and presentations. H Exam,HW
Prepared by and Date KORAY KOCABAŞ , May 2023
Course Coordinator HIZIR KONUK
Semester Fall
Name of Instructor

Course Contents

Week Subject
1) Introduction and basics
2) Data Types
3) Basic Reporting and Querying
4) Business intelligence lifecycle & building the BI Plan
5) Business intelligence lifecycle & building the BI Plan
6) 10 Keys to BI Projects
7) 10 Risks to BI Projects
8) Thinking of marketing intelligence data layer
9) Designing Data Warehouse
10) ETL Development using SSIS 1
11) ETL Development using SSIS 2
12) Developing Customer oriented data layer for marketing analytics
13) Data Visualization 1
14) Data Visualization 2
15) Final Examination Period
16) Final Examination Period
Required/Recommended ReadingsThe Data Warehouse Toolkit, Building the Data Warehouse, T-SQL Fundamentals, Professional Microsoft SQL Server 2014 Integration Services, Professional Microsoft SQL Server 2016 Reporting Services
Teaching MethodsThe methods which will be used throughout the course are real life data cultured company case studies, presentations, in-class discussions – brain storming. Every member of the class is expected to freely share her/his knowledge, ideas and questions with the group without any concern. Throughout the course, experiential, constructivist, research-based and reflective teaching strategies are used. In all kinds of teaching and learning activities, student participation, active learning and learning by doing are essential.
Homework and ProjectsThe students will be making one beginner level design a marketing based datawarehouse as a group at the end of the course
Laboratory WorkNone
Computer UsePersonal notebook
Other Activities
Assessment Methods
Assessment Tools Count Weight
Attendance 1 % 20
Quiz(zes) 1 % 30
Midterm(s) 2 % 50
TOTAL % 100
Course Administration kocabask@mef.edu.tr

Öğrenciler her zaman serbesttir ve öğretim elemanına e-posta yoluyla dersle ilgili geri bildirimde bulunmak ve soru sormak konusunda teşvik edilirler.(kocabask@mef.edu.tr). Bu derste sql komutlarını kullanarak tabloları sorgulamak, iş zekası projesinin katmanlarını tasarlamak ve anlamak, beyin fırtınası ve tartışma gibi konuların öğrenilmesi ve uygulanması için aktif katılım esastır. Böylece derse katılımın notlandırılması, öğrencinin aktif katılımının ve sınıf içi etkinliklere katkısının niteliğine göre yapılacaktır. Öğrencilerin tüm oturumlara katılmaları ve zamanında derste bulunmaları beklenmektedir. Hastalık (tam donanımlı bir hastaneden rapor gerektirir) veya MEF yönetmeliklerimde kabul edilen bir mazeret nedeniyle katılamayacakları durumlarda, eğitmenlere posta yoluyla bilgi vermeleri gerekmektedir. Geri bildirim ve sorular, kursu farklı bir öğrenme deneyimi haline getirmek için çok değerli olduğundan, öğrenciler dersle ilgili her türlü sorun için mesai saatleri içinde eğitmenleri ziyaret edebilir veya e-posta gönderebilirler. Akademik sahtekarlık ve intihal YÖK disiplin yönetmeliğine tabi olacak Students are always free and encouraged to give feedback and ask questions about the course via e-mail to instructor (kocabask@mef.edu.tr). In this course, active participation is key to learning and applying, as for a topic like querying tables using sql commands, designing and understanding the layers of business intelligence project, brain storming and discussion. Thus the grading of the class participation will be done based on the quality of active student participation and contribution to in-class activities. Students are expected to attend all sessions and be in class on time. When they can not attend due to a sickness (which should require a report from a full facility hospital) or an excuse accepted my MEF regulations, they should inform the instructors by mail. As the feedback and questions are very valuable for making the course a distinctive learning experience, students may visit the instructors during office hours or send e mails, for any course related issues. Academic dishonesty and plagiarism will be subject to the YÖK disciplinary regulation

ECTS Student Workload Estimation

Activity No/Weeks Hours Calculation
No/Weeks per Semester Preparing for the Activity Spent in the Activity Itself Completing the Activity Requirements
Course Hours 14 2 3 1 84
Project 2 8 2 20
Midterm(s) 2 8 2 20
Total Workload 124
Total Workload/25 5.0
ECTS 5