BIG DATA ANALYTICS AND MANAGEMENT (ENGLISH, NONTHESIS)
Master	TR-NQF-HE: Level 7	QF-EHEA: Second Cycle	EQF-LLL: Level 7

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
SEN5301	Introduction to Information Technologies Services Management	Spring	3	0	3	8

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Departmental Elective
Course Level:
Mode of Delivery:	Face to face
Course Coordinator :	Prof. Dr. ADEM KARAHOCA
Course Lecturer(s):	Prof. Dr. ADEM KARAHOCA
Recommended Optional Program Components:	None
Course Objectives:	This course provides an overview of IT Services. Topics include enterprise systems management (ESM), which is the complete and total management of a company's IT elements and/or environment. IT services, or ESM, involves two categorizations: infrastructure management -the discipline regarding services responsible for maintaining and managing the IT elements in an environment, and relationship management -the discipline containing the services that are customer facing in relation to their IT infrastructure.

Learning Outcomes

The students who have succeeded in this course;
1. Define computing infrastructure
2. Examine IT services
3. Define event and fault management
4. Describe problem, change and configuration management
5. Examine asset management
6. Define security and network management
7. Define storage, workload, backup and recovery management
8. Examine business process management fundamentals
9. Describe business process management supporting infrastructure

Course Content

The content of this course is composed of computing infrastructure overview, introduction to IT services, event & fault management, problem, change and configuration management, asset management, security and network management, storage, workload, backup and recovery management, business process management fundamentals, business process management supporting infrastructure.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Computing Infrastructure Overview
2)	Introduction to IT Services
3)	Event & Fault Management
4)	Problem, Change and Configuration Management
5)	Asset Management
6)	Security and Network Management
7)	Storage, Workload, Backup and Recovery Management
8)	Storage, Workload, Backup and Recovery Management / Midterm
9)	Business Process Management Fundamentals
10)	Business Process Management Supporting Infrastructure
11)	Business Process Management Supporting Infrastructure / Midterm
12)	Case Study Presentations
13)	Case Study Presentations
14)	Project Presentation

Sources

Course Notes / Textbooks:	Rob Addy, Effective IT Service Management: To ITIL and Beyond, Springer
References:	OGC- ITIL v3 references library– Service Design, Transition, Operation, Strategy, Continual Service Improvement.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	2	% 10
Homework Assignments	2	% 10
Midterms	2	% 40
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	To be able to follow and critically analyze scientific literature and use it effectively in solving engineering problems.	1
2)	To be able to design, plan, implement and manage original projects related to Big Data Analytics and Management.	1
3)	To be able to carry out studies on Big Data Analytics and Management independently, take scientific responsibility and critically evaluate the results obtained.	2
4)	Effectively present the results of his/her research and projects in written, oral and visual form in accordance with academic standards.	1
5)	To be able to conduct independent research in the field of Big Data Analytics and Management, develop original ideas and transfer this knowledge to practice.	1
6)	Uses advanced theoretical and practical knowledge specific to the field of Big Data Analytics and Management effectively.	1
7)	Acts in accordance with professional, scientific and ethical values; takes responsibility by considering the social, environmental and ethical impacts of engineering applications.	2