Instructor: Dr. Liping Liu, College of Business Administration Building 360, 330-972-5947, liping@uakron.edu
Textbooks:
- Wilfried Lemahieu, Seppe vanden Broucke, and Bart Baesens, Principles of Database Management: The Practical Guide to Storing, Managing and Analyzing Big and Small Data 1st Ed., Cambridge University Press, (ISBN: 978-1107186125)
- Liping Liu, Database Design and Management using Tools, available on ecourse.org
Time and Location: Wednesdays, August 28-December 10, 2024. Regular Classroom: CBA 176 (Computer Lab).
Office Hours: 1:30 – 3:30 PM Mondays and Wednesdays
Course Description: This is an introductory course to database design and management. It covers the issues of database management, Data Modeling, Relational Database Theory, Structured Query Language (SQL), and non-SQL databases. Optional topics may include data warehouse design, PL/SQL programming, database programming using C#, Java, or Visual Basic, and ASP.NET.
Philosophy: Differently from an undergraduate database course, this course aims at the understanding of database management issues, the design of real databases, and application of database technologies. However, basic database concepts such as relational database theory and programming skills such as structured query language will have to be thoroughly introduced in order to achieve the goal. DBMS tools are used to enhance the learning of concepts and logics.
Course Objectives: Upon satisfactory completion of this course, a student should be able to
- Understand database concepts, database management issues, and systems development processes
- Apply data modeling technique, and the concepts of data-integrity and normal forms to design databases for real businesses
- Implement a database design using Microsoft Access and Oracle
- Perform intermediate Oracle database administration tasks
Weekly Schedule:
- Week 1: Database Concepts and Data Modeling using Oracle Data Modeler®
- Week 2: Labor Day (no class)
- Week 3: Relational Models and Forward Engineering
- Week 4: Advanced Data Modeling (recursive relationships, weak entities, associative entities) and Forward Engineering
- week 5: SQL: Database Implementation in Oracle using DDL and Oracle SQL Developer®
- Week 6: Normal Forms: 1NF, 2NF, and 3NF
- Week 7: Normal Forms: BCNF
- Week 8: Midterm Exam
- Week 9: SQL: Simple Queries, Multiple Table Queries, Using Criteria, Sorting
- Week 10: SQL: Expressions and Group Functions
- Week 11: Sub-queries
- Week 12: SQL: Hierarchical Queries, Tuple Variables, and Text Search
- Week 13: NoSQL Database: JASON structure and Basic MongoDB Queries
- Week 14: NoSQL Database: Advanced MongoDB Queries
- Week 15: Final Exam (6:00-8:00PM, Wednesday, December 11, 2024)
Exams: This course will have two major exams as scheduled above. Each exam includes both hands-on and written problems.
Assignments: Homework is assigned once a week for 12 weeks; each consists of conceptual questions and hands-on projects classified into three grading categories: correctness, closeness, and completeness. The correctness problems will be graded by ecourse.org, and closeness questions are graded and/or commented by instructors. Students will earn points automatically for each completeness question if it is finished (it has to be deemed complete). Assignments are due at the beginning of each class meeting. No late homework will be graded. In addition, a semester-long project is assigned at the beginning of the course and due in the last class. Please show your work in a neat and orderly fashion. If it is a written assignment, write or type your work on one side and in every other line. Use standard size paper (8 1/2'' by 11''). Do not use spiral notebook paper.
Attendance: Attendance is MUST and will be 10% of your final grade. Attendance will be managed by ecourse.org system. The formula for computing your attendance grade is non-linear. It will take 3 points off for the first absence and 7 points off for second absence. If you missed the equivalent of three-week classes, you fail the course automatically. Under special situations, you can take some classes online with the following guidelines:
- You must obtain permission from the instructor at least one day ahead of each online session
- Follow the lectures or recordings to perform all in-class hands-on exercises and take notes. Within one day from the class submit your notes and the finished exercises to ecourse.org as Proof of Attendance.
- All weekly assignments are due at the same time as in-person classes. All exams must be onsite.
Quizzes: I will use quizzes regularly to check your completion or preparation of assignments.
Makeup: Each student with appropriate excuses may have at most one chance to makeup homework or quiz. Note that it is your privilege but not right to have this special favor. Also, all makeups must be completed within one week of due date and before answer key is released.
Grades: Your final grades will be calculated by the following formulas:
40% (HW) + 50% (Tests or Projects) + 10% (Attendance)
A = 93-100%; A– = 90-92%; B+ = 87-89%; B = 83-86%; B– = 80-82%; C+ = 77-79%; C = 73-76%; C– =70-72%; D = 60-69%; F = 59% and less
Misconduct: Academic misconduct by a student shall include, but not limited to: disruption of classes, giving and receiving unauthorized aid on exams or in the preparation of assignments, unauthorized removal of materials from the library, or knowingly misrepresenting the source of any academic work. Academic misconduct by an instructor shall include, but not limited to: grading student work by criteria other than academic performance or repeated and willful neglect in the discharge of duly assigned academic duties.
On Collaboration: All for-credit assignments, except for those designated as group projects, must be done independently, and collaboration in providing or asking for answers to those assignments constitutes cheating.
On AI Tools: In this class, I allow students to use AI tools to help their learning. However, submitting AI generated work for credits is a violation of academic code. If a submitted work is suspected to be AI generated, the student will be asked to reproduce the submitted work in front of the instructor.
School Rule Cited: For graduate students that have been caught cheating: First offense = either a zero on the exam or assignment, or an F in the course; Second offense = Either an F in the course or expulsion (depending upon the punishment of the first offense)
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