Information Package / Course Catalogue
| Business Administration | |||||
| Bachelor | Length of the Programme: 4 | Number of Credits: 240 | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF: Level 6 |
Ders Genel Tanıtım Bilgileri
| School/Faculty/Institute | Faculty of Econ., Admin. and Social Sciences | ||||
| Course Code | MGMT 431 | ||||
| Course Title in English | Business Intelligence | ||||
| Course Title in Turkish | Business Intelligence | ||||
| Language of Instruction | EN | ||||
| Type of Course | Seçiniz | ||||
| Level of Course | Seçiniz | ||||
| Semester | Fall | ||||
| Contact Hours per Week |
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| Estimated Student Workload | 124 hours per semester | ||||
| Number of Credits | 5 ECTS | ||||
| Grading Mode | Standard Letter Grade | ||||
| Pre-requisites |
MIS 301 - Management Information Systems |
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| 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 CompetencesUpon 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) Has a broad foundation and intellectual awareness with exposure to mathematics, history, economics, and social sciences | |||||
| 2) Demonstrates knowledge and skills in different functional areas of business (accounting, finance, operations, marketing, strategy, and organization) and an understanding of their interactions within various industry sectors | |||||
| 3) Applies theoretical knowledge as well as creative, analytical, and critical thinking to manage complex technical or professional activities or projects | |||||
| 4) Exhibits an understanding of global, environmental, economic, legal, and regulatory contexts for business sustainability | |||||
| 5) Demonstrates individual and professional ethical behavior and social responsibility | |||||
| 6) Demonstrates responsiveness to ethnic, cultural, and gender diversity values and issues | |||||
| 7) Uses written and spoken English effectively (at least CEFR B2 level) to communicate information, ideas, problems, and solutions | |||||
| 8) Demonstrates skills in data and information acquisition, analysis, interpretation, and reporting | |||||
| 9) Displays computer proficiency to support problem solving and decision-making | |||||
| 10) Demonstrates teamwork, leadership, and entrepreneurial skills | |||||
| 11) Displays learning skills necessary for further study with a high degree of autonomy |
Relation to Program Outcomes and Competences
| N None | S Supportive | H Highly Related |
| Program Outcomes and Competences | Level | Assessed by | |
| 1) | Has a broad foundation and intellectual awareness with exposure to mathematics, history, economics, and social sciences | S | Exam |
| 2) | Demonstrates knowledge and skills in different functional areas of business (accounting, finance, operations, marketing, strategy, and organization) and an understanding of their interactions within various industry sectors | S | Exam |
| 3) | Applies theoretical knowledge as well as creative, analytical, and critical thinking to manage complex technical or professional activities or projects | H | Exam |
| 4) | Exhibits an understanding of global, environmental, economic, legal, and regulatory contexts for business sustainability | N | |
| 5) | Demonstrates individual and professional ethical behavior and social responsibility | N | |
| 6) | Demonstrates responsiveness to ethnic, cultural, and gender diversity values and issues | N | |
| 7) | Uses written and spoken English effectively (at least CEFR B2 level) to communicate information, ideas, problems, and solutions | N | |
| 8) | Demonstrates skills in data and information acquisition, analysis, interpretation, and reporting | H | HW |
| 9) | Displays computer proficiency to support problem solving and decision-making | H | Project |
| 10) | Demonstrates teamwork, leadership, and entrepreneurial skills | N | |
| 11) | Displays learning skills necessary for further study with a high degree of autonomy | S | HW |
| Prepared by and Date | KORAY KOCABAŞ , May 2023 |
| Course Coordinator | CEYHAN MUTLU |
| Semester | Fall |
| Name of Instructor | Öğr. Gör. KORAY KOCABAŞ |
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 Readings | The 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 Methods | The 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 Projects | The students will be making one beginner level design a marketing based datawarehouse as a group at the end of the course | |||||||||||||||
| Laboratory Work | None | |||||||||||||||
| Computer Use | Personal notebook | |||||||||||||||
| Other Activities | ||||||||||||||||
| Assessment Methods |
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| Course Administration |
kocabask@mef.edu.tr 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 |
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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 | ||||||