Information Package / Course Catalogue
Advanced Data Management
Course Code: YZO259
Course Type: Area Elective
Couse Group: Short Cycle (Associate's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 4
Objectives of the Course

This course introduces data storage and processing at desktop and cloud scales. It introduces fundamental database concepts and provides a practical introduction to both SQL and NoSQL systems. The goal of this course is to introduce students to various platforms and techniques for managing big data beyond what traditional transactional databases can handle.

Course Content

Introduction to Data Management Data Models: From Traditional to Graph Databases SQL and NoSQL: MySql and MongoDB Big Data Sources and Types Scalable Methods for Big Data Analysis Parallel and Distributed Computing Concepts for Data Management Data Visualization and Analysis Hadoop and MapReduce

Name of Lecturer(s)
Learning Outcomes
1.Understanding the shortcomings of traditional database management systems when handling emerging applications with complex data requirements
2.Explain the similarities and differences between transactional and non-transactional data
3.Explain the differences and advantages of each of the two transaction concepts called ACID and BASE.
4.Understanding the difference between various NoSQL data management platforms and where each is more useful and applicable
5.Leveraging emerging advanced platforms (such as HADOOP and SPARK) to manage non-transactional data
Recommended or Required Reading
1.“Database Systems: A practical Approach to Design, Implementation, and Management”, T. Collony & Carolyn Begg, 5th Edition, Addison-Wesley, 2010.
Weekly Detailed Course Contents
Week 1 - Theoretical
Data Models: from traditional to graph databases
Week 2 - Theoretical
SQL and NoSQL: MySql and MongoDB
Week 3 - Theoretical
Concurrency Control Techniques
Week 4 - Theoretical
Object-Oriented and Object-Relational Databases
Week 5 - Theoretical
Semi-Structured Data and XML
Week 6 - Theoretical
Parallel and Distributed Databases
Week 7 - Theoretical
Distributed Databases-Advanced Concepts
Week 8 - Theoretical
Big data sources and types (midterm exam)
Week 9 - Theoretical
Scalable methods for big data analysis
Week 10 - Theoretical
Parallel and Distributed Computing Concepts for data management
Week 11 - Theoretical
Data Visualization and Analysis
Week 12 - Theoretical
Big Data - Apache Hadoop, MapReduce & Pig Latin
Week 13 - Theoretical
Big Data - Apache Hadoop, MapReduce & Pig Latin
Week 14 - Theoretical
Temporary Databases
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%10
Quiz1%10
Midterm Examination1%20
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Assignment116117
Quiz116117
Midterm Examination116117
Final Examination120121
TOTAL WORKLOAD (hours)100
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
OÇ-1
5
5
5
5
4
4
4
4
4
2
2
3
OÇ-2
5
5
5
5
5
5
5
4
4
3
3
4
OÇ-3
5
5
5
4
4
4
3
4
4
3
2
4
OÇ-4
5
5
5
4
4
4
5
4
5
3
3
4
OÇ-5
4
4
4
5
5
5
4
4
5
2
2
3
Adnan Menderes University - Information Package / Course Catalogue
2026