CS7260 Advanced Database Systems

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Abraham Silberschatz
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KSU/SPSU Consolidation Course Proposal for Curriculog
Fall 2014 Approval for Fall 2015 Implementation
College
Department
Program
Course Prefix and Number
Course Title
Credit Hours
Prerequisite(s)
Area
Course Description
Learning Objectives for this
course
Contribution of the course
to the program outcomes
Assessment plan and
process
College of Computing and Software Engineering
Computer Science
Master Science in Computer Science
CS7260
Advanced Database Systems
3
CS5060 or equivalent
__Area F __ Major Required _x_ Major Elective
This course will cover advanced concepts and techniques in database
systems. Topics include advanced concepts in relational databases, data
warehousing and mining, and NoSQL distributed database technology
for big data analytics.
Upon the completion of this course, students should be able to
1. write advanced SQL queries
2. optimize relational database queries
3. develop data warehousing systems
4. conduct OLAP and data mining
5. explain NoSQL concepts
6. develop distributed systems for big data analytics
1. Demonstrate an advanced understanding of the capabilities and limits of
computation, hardware
and software systems, and software development
2. Analyze complex problems in the computing discipline and design
solutions that integrate
hardware and software, and that are technologically appropriate and
theoretically sound
Evaluation will be through exams, homework assignments and course
projects. Evaluation will consist of:
Midterm Exam:
25%
Final Exam:
25%
Homework assignments:
25%
Course project
25%
100%
Instruction Delivery
Method
_x_ Traditional On Campus
_x_ Fully Online
__ Quality Matters Approved
__ Hybrid (describe)
Proposal Lead Author
Funding Required
Lab Fees or special tuition
Ying Xie
NA
NA
CS 7260 Advanced Database Systems Syllabus
3 Class Hours, 0 Laboratory Hours, 3 Credit Hours
Course Description: This course will cover advanced concepts and techniques in database systems.
Topics include advanced concepts in relational databases, data warehousing and mining, and NoSQL
distributed database technology for big data analytics.
Instructor: TBD
Learning Objectives:
Upon the completion of this course, students should be able to
 write advanced SQL queries
 optimize relational database queries
 develop data warehousing systems
 conduct OLAP and data mining
 explain NoSQL concepts
 develop distributed systems for big data analytics
Textbook and Learning Materials:
1. Abraham Silberschatz, Henry Korth and S. Sudarshan, Database System Concepts
McGraw-Hill Science/Engineering/Math; 6/e, ISBN 0073523321, 2010
2. Online Materials
Instructional Delivery Methods and Attendance Policy: This course will have in-classroom
lectures and also provide both synchronous and asynchronous distance learning options.
Course Requirements and Assignments: Students will be expected to attend all classes in
classroom or through distance learning delivery, work on homework assignments and course project,
and take all exams.
Evaluation and Grading: Evaluation will be through exams, homework assignments and course
projects. Evaluation will consist of:
Midterm Exam:
Final Exam:
25%
25%
Homework assignments:
Course project
25%
25%
100%
Academic Honesty Statement: Every KSU student is responsible for upholding the provisions of the
Student Code of Conduct, as published in the Undergraduate and Graduate Catalogs. Section II of the
Student Code of Conduct addresses the University's policy on academic honesty, including provisions
regarding
plagiarism
and
cheating,
unauthorized
access
to
University
materials,
misrepresentation/falsification of University records or academic work, malicious removal, retention, or
destruction of library materials, malicious/intentional misuse of computer facilities and/or services, and
misuse of student identification cards. Incidents of alleged academic misconduct will be handled
through the established procedures of the University Judiciary Program, which includes either an
"informal" resolution by a faculty member, resulting in a grade adjustment, or a formal hearing
procedure, which may subject a student to the Code of Conduct's minimum one semester suspension
requirement.
Students are encouraged to study together and to work together on course projects as per the
instructor’s specifications; however, the provisions of the STUDENT CONDUCT REGULATIONS, II.
Academic Honesty, KSC Undergraduate Catalog will be strictly enforced in this class.
Students are required to work INDEPENDANTLY on homework assignments and online exams.
Schedule and Topic Coverage:
Week
1
2
3
4
5
6
7
8
9
10
10
11
12
13
14
16
Lecture Topic
Reference
Introduction
Query Processing
Query Optimization
Transaction Management 1
Chapter 12
Chapter 13
Chapter 14
Transaction Management 2
Data Warehousing 1
Data Warehousing 2
Midterm Exam
Data Mining 1
Data Mining 2
Intro to NoSQL Databases
MongoDB 1
MongoDB 2
Cassandra 1
Cassandra 2
Chapter 14
Chapter 20
Chapter 20
Exam
Chapter 20
Online Material
Online Material
Online Material
Online Material
Online Material
Online Material
As per Semester
Schedule
Final Exam
×

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