Instructor : Dr. Sreyasee Das Bhattacharjee
Office: Davis Hall 349
Office Hour: Wed 5:00 p.m. - 6:00 p.m. or by appointment
General Information
Lectures: Mon, Wed, Fri 4:00 p.m. - 4:50 p.m.
Room: Hoch 114
TA(s):
- Yufan Zhou (yufanzho@buffalo.edu ; Office Hour: Mon, Fri, 9:00 a.m. - 10:00 a.m.);
- Xian Zhou (xianzhou@buffalo.edu ; Office Hour: Wed, 2:30 p.m. - 3:30 p.m., Thu, 1:45 p.m. - 2:45 p.m.);
- Jyoti Sinha (jsinha@buffalo.edu ; Office Hour: Tue, 2:00 p.m. - 3:00 p.m., Thu, 3:00 p.m. - 4:00 p.m.);
Piazza: We will use Piazza to answer questions and post announcements about the course. Please sign up here.
Prerequisites: Basic data stucture; Good programming skills in at least 1 language (C++, Java, Python).
Course Overview: Data Management Systems form the basis of the Big Data Economy we now live in. A data management system is responsible for storing data, enabling efficient access to that data, as well as mediating concurrent modifications. This class approaches the challenges of designing a data management system from a standpoint that is both principled and practical. Students will be introduced to the fundamental data management issues: database design, query languages, database file organization, query processing and optimization, transaction processing. Course lectures will focus on the conceptual basis for this system and how they form the foundations for implementing efficient algorithms of data mining and other data analytic tasks.
Textbooks:
- Database System Concepts (7th Edition) by Abraham Silberschatzm et al.;
- Database Systems: The Complete Book (2nd Edition) by Hector Garcia-Molina et al.;
- Database Management Systems (3rd Edition) by Raghu Ramakrishnan and Johannes Gehrke;
Grade Composition:
- Biweekly assignment: 30%;
- Programming Assignment: 20%;
- Midterm: 25%;
- Final: 25%;
- Bonus on Class Activity: 5%;
Course Schedule (Tentitive):
| Week | Lecture | Announcement |
|---|---|---|
| Week 1 | Introduction and Overview | |
| Week 2 | Intermediate SQL | First Assignment (Due Date: 2/17/2020) |
| Week 3-5 | Advanced SQL | |
| Week 6-7 | Database Design | |
| Week 8 | Spring Break | |
| Week 9-11 | Indexing | |
| Week 12-13 | Transaction Processing | |
| Week 14 | Parallel&Distributed Database | |
| Week 15 | Data Mining&Information Retrieval |
Academic Integrity:
- (Short) Don't cheat! You will be caught and punished. Our department is serious about graduating ethical and upstanding computer scientists. The policy has recently been updated and will be enforced.
- (Long) All academic work must be your own. Plagiarism, defined as copying or receiving materials from a source or sources and submitting this material as one's own without acknowledging the particular debts to the source (quotations, paraphrases, basic ideas), or otherwise representing the work of another as one's own, is never allowed. Collaboration, usually evidenced by unjustifiable similarity, is never permitted in individual assignments. Any submitted academic work may be subject to screening by software programs designed to detect evidence of plagiarism or collaboration. Also, do not post any of the course material outside of the Course piazza page. It will be interpreted as an attempt to get non-approved help.
Special Accommodations: In case of need of special accommodations please go the following link for more information: Special Accommodations