2019 Fall Semester

ISE4028-Database Analysis and Design (데이터베이스분석설계)

Instructor: Dr. Muhammad Syafrudin

Course information

Databases are everywhere. Data is a crucial resource for most organizations, so effective storage and access of that data is an important concern. This course is intended to introduce the student to the important principles of database management systems and the design of databases. In addition, the student will gain experience working with practical database management package: Oracle. In the end, the students are expected to be able to apply the database to real-world problems based on the theory and practice-based learning.

On successful completion of the course students will be able to:
• Understand the benefits of database management systems.
• Understand the process of data modeling including the entity-relationship approach.
• Understand the principles that should be used in designing a relational database, including normalization techniques.
• Gain some exposure and experience with a commercial relational database management system (RDBMS).
• Define and set up a relational database using the RDBMS.
• Gain experience working on a database application development.
• Understand how to define database structures and how to specify database queries using SQL, and gain experience writing SQL queries on a practical system.


Wed (수) at 4:30‐7:15 pm in 원흥관 F305 ERP실습실

**Office Hours

Tue–Fri (10am–6pm) at 산업 AI 연구센터 or 동국대학교충무로영상센터 본관 825호.

Course material can be downloaded in e-Class and please be aware, that we will not publicly release the homework assignments this year.


No prior programming experience is required. This course will teach your from the very basic and gradually increase to the next level.


We will be using Oracle XE Database. More details will be provided in the class.

Course Activities

The course is structured in two different types of activities that repeat themselves each week and they are: 50% Lectures and 50% Labs which be held on Wed.

  1. Lectures material will be provided to introduce the students about basic concept or theory about each topic weekly. There will be quizzes at the end of each lecture to assess the understanding of the material that will help us identify gaps.

  2. Labs are designed as hands-on activities and are useful to practice with problems similar to the homework.

Supplementary Textbook or E-book (Optional)

  • Kroenke and Auer: Database Processing: Fundamentals, Design, and Implementation, 13th Edition.


주차(Week) 강의내용(Class Topic & Contents) 강의활동유형(Class Type)
1 Course introduction and prospects 강의 (Lecture)
2 Introduction to Database 강의+실습 (Lecture + Practice)
3 Structured Query Language (SQL) 1 강의+실습 (Lecture + Practice)
4 Structured Query Language (SQL) 2 강의+실습 (Lecture + Practice)
5 Relational Model and Normalization 강의+실습 (Lecture + Practice)
6 Database Design Using Normalization 강의+실습 (Lecture + Practice)
7 Data Modeling with the Entity-Relationship Model 강의+실습 (Lecture + Practice)
8 Mid exam 시험 (Exam)
9 Transforming Data Models into Database Designs 강의+실습 (Lecture + Practice)
10 SQL for Database Construction and Application Processing 강의+실습 (Lecture + Practice)
11 Database Redesign 강의+실습 (Lecture + Practice)
12 The Web Server Environment (Apache Web Server) 강의+실습 (Lecture + Practice)
13 The Web Development 1 (PHP + Database) 강의+실습 (Lecture + Practice)
14 The Web Development 2 (PHP + Database + Bootstrap) 강의+실습 (Lecture + Practice)
15 Final exam 시험 (Exam)

Grading Formula

The final grade will be calculated using the following weights:

# Final Grade Weight
Attendance 15%
Assignment(quiz/homework/weekly assignment) 15%
Mid exam (closed-book) 30%
Final exam (closed-book) 40%
Total 100%


There will be a quiz/homework/weekly assignment to complete. Some of them will be due in a week and some of them in two weeks. You have the option to work and submit the homework in pairs for all the assignments except two which you will do individually. The homework are graded on a scale 0 to 100, where 100 is the highest grade.

Submitting an Assignment

Instructions for turning in assignments will be posted when the semester starts (in e-Class).

Getting Help

For questions about homework, course content, package installation, and after you have tried to troubleshoot yourselves, the process to get help is:

  1. Post the question in e-Class and hopefully your peers will answer. Note that in e-Class questions are visible to everyone.
  2. For private matters send an email to helpline: udin [at] dongguk [dot] edu.

Course Policies

Collaboration Policy

We encourage you to talk and discuss the assignments with your fellow students (and on e-Class), but you are not allowed to look at any other students assignment or code outside of your pair. Discussion is encouraged, copying is not allowed.

Late Day Policy

Homework is due on Tuesdays. Late submission are not allowed.

Communication to Students

Class announcements will be through e-Class. All homework and quizzes will be posted and submitted in e-Class. Also all feedback forms. Important note: make sure you have your settings set so you can receive emails from e-Class.

Academic Honesty

Ethical behavior is an important trait of a Data Scientist, from ethically handling data to attribution of code and work of others. Thus, in ISE we give a strong emphasis to Academic Honesty. As a student your best guidelines are to be reasonable and fair. We encourage teamwork for problem sets, but you should not split the homework and you should work on all the problems together.