Fall 2019
Database Design and Analysis
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. Furthermore, the class will be delivered in English.
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.
Lecture
Wednesday (수) at 16.30 – 19.15 KST in 원흥관 F305 ERP실습실
Office hours
Tue–Fri (10am–6pm) at 산업 AI 연구센터 동국대학교충무로영상센터 본관 825호.
Prerequisites
ISE4025 정보시스템분석설계 (Information System) or equivalent
Software
We will be using Oracle Database XE run on the computer lab (in ERP room) or on your own machine. 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.
- 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.
- Labs are designed as hands-on activities and are useful to practice with problems similar to the homework.
Notes
Course material can be downloaded in e-Class and please be aware, that we will not publicly release the homework assignments this year.
Supplementary textbook or e-book (optional)
Kroenke and Auer: Database Processing: Fundamentals, Design, and Implementation, 13th Edition.
Schedule
| 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
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% |
Assignment
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:
Post the question in e-Class and hopefully your peers will answer. Note that in e-Class questions are visible to everyone. 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 Wednesday before class. Late submission are not allowed.
Communication to students
Class announcements will be through e-Class. All homework and quizzes will be posted 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.