Advanced Databases (CMPE541) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Advanced Databases CMPE541 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The objective of this course is to introduce students to advanced concepts of designing and implementing database systems.
Course Learning Outcomes The students who succeeded in this course;
  • Discuss transaction processing, concurrency control and database recovery.
  • Review object-oriented and object-relational databases.
  • Describe semi-structured data and XML.
  • Discuss parallel and distributed databases.
  • Explain big data and temporal databases.
Course Content Database system concepts, transaction processing, concurrency control and database recovery, object-oriented and object-relational databases, semi-structured data and XML, parallel and distributed databases, advanced concepts of distributed databases, introduction to big data, temporal databases.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction Lecture Notes
2 Transaction Processing Concepts Lecture Notes Chapter 20 (Text Book 1) Chapter 17 (Text Book 2)
3 Transaction Processing Concepts Lecture Notes Chapter 20 (Text Book 1) Chapter 17 (Text Book 2)
4 Concurrency Control Techniques Lecture Notes Chapter 20 (Text Book 1) Chapter 18 (Text Book 2)
5 Concurrency Control Techniques Lecture Notes Chapter 20 (Text Book 1) Chapter 18 (Text Book 2)
6 Database Recovery Techniques Lecture Notes Chapter 20 (Text Book 1) Chapter 19 (Text Book 2)
7 Object-oriented and Object-relational databases Lecture Notes Chapter 26, 27, 28 (Text Book 1) Chapter 10 (Text Book 2)
8 Semi-structured data and XML Lecture Notes Chapter 30 (Text Book 1) Chapter 11 (Text Book 2)
9 Semi-structured data and XML Lecture Notes Chapter 30 (Text Book 1) Chapter 11 (Text Book 2)
10 Parallel and Distributed Databases Lecture Notes Chapter 22 (Text Book 1) Chapter 20 (Text Book 2)
11 Distributed Databases – Advanced Concepts Lecture Notes Chapter 23 (Text Book 1)
12 Distributed Databases – Advanced Concepts Lecture Notes Chapter 23 (Text Book 1)
13 Big Data – Apache Hadoop, MapReduce & Pig Latin Lecture Notes
14 Temporal Databases Lecture Notes
15 Review
16 Review

Sources

Course Book 1. “Database Systems: A practical Approach to Design, Implementation, and Management”, T. Collony & Carolyn Begg, 5th Edition, Addison-Wesley, 2010.
2. Database Systems: The Complete Book, 2nd Ed, Garcia-Molina, Ullman and Widom, Pearson, 2008.
Other Sources 3. “Fundamentals of Database Systems”, 5th Edition, Ramez Elmasri & Shamkant B. Navathe, Addison-Wesley, 2006.
4. Apache Hadoop Project, available at http://hadoop.apache.org/

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project 3 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 35
Final Exam/Final Jury 1 35
Toplam 5 100
Percentage of Semester Work 65
Percentage of Final Work 35
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Gains the ability to apply advanced computing and/or information knowledge in solving software engineering problems. X
2 Develops solutions using different technologies, software architectures and life-cycle approaches. X
3 Gains the ability to design, implement, and evaluate a software system, component, process, or program using modern techniques and engineering tools for software engineering practices. X
4 Gains ability to gather/acquire, analyze, interpret data and make decisions to understand software requirements. X
5 Gains skills of effective oral and written communication and critical thinking about a wide range of issues arising in the context of working constructively on software projects. X
6 Gains the ability to access information to follow current developments in science and technology, conducts scientific research in the field of software engineering, and conducts a project.
7 Acquires an understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering.
8 Acquires project and risk management skills and gains awareness of the importance of entrepreneurship, innovation, and sustainable development, as well as international standards and methodologies. X
9 Understands the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions.
10 Gains awareness of the development, adoption, and ongoing support for the use of excellence standards in software engineering practices. X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 3 48
Presentation/Seminar Prepration
Project
Report
Homework Assignments 3 4 12
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 8 8
Prepration of Final Exams/Final Jury 1 14 14
Total Workload 130