Instructor: David Yang (Science South 450, david.yang@csueastbay.edu)
Time: Mondays, Wednesdays 6PM-7:50PM
Location: Online (Mondays), South Science 125 (Wednesdays). As a hybrid course, we will be meeting on campus only once a week (Wednesday), but you are expected to be online on Mondays, during which we will work on lab exercises. Because we are surveying fairly different topics within databases, you will need to install some free/trial software on a home machine. You are expected to do this before the Monday class. If your home network connection is slow, you will probably want to download it at school or elsewhere, then bring it home to install. We will use Blackboard's chatroom tool for Monday classes to provide some initial step-by-step guidance, then more individual questions once we have gotten through the start of the lab exercise.

Blackboard:
Here is a page with useful info related to Blackboard.

Text:
I will make some use of Silberschatz, Korth and Sudarshan, Database System Concepts, but there will be plenty of Internet material, and a recent edition of any of the standard texts (Date, Ullman, etc.) probably includes some material on many of the topics. There is a 5th edition of Silberschatz et al., but the 4th edition should be fine. We will be using Oracle for most of the Monday exercises, so we will make fairly substantial use of the Oracle documentation, which you can download or simply read through online. Most of the work will be designed around Oracle Express (also known as Oracle XE) 10g. It requires about 1.1 GB of disk space to install. If you happen to have the whole Oracle 10g or 11g on your computer, that would obviously work, too.

Goals:

• to further explore the database topics of a standard undergraduate course. Databases have evolved quite a bit, and these topics will not always "look like" databases. To solve various problems, the newer topics draw from not only databases, but data structures, programming language concepts, artificial intelligence, statistics, operating systems, among other areas.
• To gain some experience with how companies that support databases are providing support for these newer topics.
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Calculation of your grade: 
Assignments : 50%.
The midterm : 20% (November 7)
The comprehensive final exam : 30%.

[grading note: Your exams must average (using the relative weights above) out to a B- or better in order to get at least a B- in the course.]

Final grades will be given according to the following scale:

93-100 A, 90-92 A-, 87-89 B+, 83-86 B, 80-82 B-, 77-79 C+, 73-76 C, 70-72 C-,67-69 D+, 60-66 D, 0-59 F 

Attendance:
Remember that standard policy dictates that students who do not attend can be removed in favor of students on the waiting list who do show up. Also, not being prepared for an exam is not an excuse to not show up -- if you do not have a verified excuse, you will be given a zero for the exam. If you find out in advance that you will not be able to be present on the day of the exam, you should (as in all your courses) let me know as soon as possible.

Academic Honesty: This course will follow the University's standard policy on academic dishonesty. In particular, note that regardless of whether you copy work from another student or allow another student to copy your work on an exam, you are both equally guilty and equally penalized. Copying text/files off the internet without properly giving credit is also cheating. Any cheating on an exam results in an F for the course. Cheating twice also results in an automatic F. All instances of cheating will be reported to the Dean's office.

Remember that the University may inflict further penalties than listed here under the provisions of the published Academic Dishonesty Policy. 

Office Hours: My office is in room 450 of the South Science Building. My schedule for office hours this semester is: 

• Monday, Wednesday 2:40-3:50pm
• Friday 11:00-11:50am

I will also be available at other times -- if I'm free, you should feel free to stop by with any questions you have. You can make an appointment to make sure I'm available and free at that time, but it's not a big deal. This is the only source of individualized attention you get, so use it.

Tentative Topic Schedule (planned timeframe -- 1 topic per week)

1. Database models : relational vs. object-relational
2. More on data modeling: spatial data
3. More on data modeling: XML
4. Data mining
5. Data warehouses
6. User Interfaces
7. Performance
8. Persistence packages vs. SQL -- Java Persistence API, Glassfish implementation
9. Heterogeneous databases
10. Frameworks -- Django