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BIG DATA MANAGEMENT PROGRAMME COURSE DESCRIPTION

Code Name of the Course Unit Semester In-Class Hours (T+P) Credit ECTS Credit
YEM435 BIG DATA MANAGEMENT 7 3 3 7

GENERAL INFORMATION

Language of Instruction : Turkish
Level of the Course Unit : BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course : Compulsory
Mode of Delivery of the Course Unit -
Coordinator of the Course Unit Assoc.Prof. TAYLAN MARAL
Instructor(s) of the Course Unit Assist.Prof. SÜREYYA İMRE BIYIKLI
Course Prerequisite No

OBJECTIVES AND CONTENTS

Objectives of the Course Unit: This course aims to provide the students with the necessary information to learn about the difficulties encountered in dealing with Big data, to comprehend the big data storage systems and to learn evaluating the different types of big data.
Contents of the Course Unit: Contents of the course include the subjects such as assessment and evaluation of media contents, database systems, new architectures and design decisions of big data processing systems, processing methods of large-scaled structured data, large-scale data flow, pipeline in big data processing.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)

Distinguish the differences between qualitative and quantitative data.
Apply the processing methods of large-scale structured data.
Produce news by making the complex data meaningful.
Create new architectures of big data processing systems.

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY

Week Preparatory Topics(Subjects) Method
1 Literature Review Introduction to Big Data Concept Lecture
2 Literature Review Big Data and New Media Relation Demonstrating & Demonstrating with samples
3 Literature Review Description of Media Contexts Demonstrating & Demonstrating with samples
4 Literature Review, Using Visual Sources Database Systems and Data Performance Analysis Demonstrating & Demonstrating with samples
5 Literature Review, Using Visual Sources MapReduce Framework Demonstrating & Demonstrating with samples
6 Literature Review, Using Visual Sources Apache Spark Demonstrating & Demonstrating with samples
7 Literature Review, Using Visual Sources Big SQL Systems Demonstrating & Demonstrating with samples
8 - MID-TERM EXAM -
9 Literature Review, Using Visual Sources General Revision Demonstrating & Demonstrating with samples
10 Literature Review, Using Visual Sources Large-scale Graphics Demonstrating & Demonstrating with samples
11 Literature Review, Using Visual Sources Large-scale Flow Operation Demonstrating & Demonstrating with samples
12 Literature Review, Using Visual Sources Large-scale Flow Operation Platforms Demonstrating & Demonstrating with samples
13 Literature Review, Using Visual Sources Disintegration of Big Data Operations in Pipeline Demonstrating & Demonstrating with samples
14 Literature Review, Using Visual Sources Discussion on advanced applications in the field Demonstrating & Demonstrating with samples
15 Literature Review, Using Visual Sources Discussion on advanced applications in the field Demonstrating & Demonstrating with samples
16 - FINAL EXAM -
17 - FINAL EXAM -

SOURCE MATERIALS & RECOMMENDED READING

Sakr S., Gaber M. M. (2014). Large Scale and Big Data. Florida: An Auerbach Book
Marr B. (2017). Buyuk Veri Is Basinda. Istanbul: Mediacat Books
Davis K. (2016). Ethics of Big Data: Balancing Risk and Innovation. California: O'Reilly Media
Bilgi ve Belge Araştırmaları Dergisi. İstanbul: İstanbul Üniversitesi

ASSESSMENT

Assessment & Grading of In-Term Activities Number of Activities Degree of Contribution (%) Description
Level of Contribution
0 1 2 3 4 5

CONTRIBUTION OF THE COURSE UNIT TO THE PROGRAMME LEARNING OUTCOMES

KNOWLEDGE

Theoretical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
List the history of communication, mass media, communication theories and leading theorists.
1
2
List the historical, social and cultural types of communication and explain the related concepts.
1
3
Define the important points of the history and theories of communication through daily life practices and social life.
1

KNOWLEDGE

Factual

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Compare the traditional media and new media economic policies.
2
2
Interpret digital culture with constantly updated and self-renewing topics.
3
3
Interpret the technical, socio-political and legal aspects of cyber security issues in the field of new media.
4

SKILLS

Cognitive

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Define the basic concepts of communication history, communication theories, traditional and new media channels.
1

SKILLS

Practical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Prepare web pages with CSS codes.
0
2
Produce creative content in new media environments, create an image and sound and practical studies about programming.
2
3
Analyze the sub-texts and their semantics of the studies presented to the society by mass media.
1
4
Use qualitative and quantitative elements to construct arguments on studies in the field of communication.
4

OCCUPATIONAL

Autonomy & Responsibility

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Manage social media accounts of brands, corporate firms and public institutions thanks to its advanced knowledge in content production and user experience.
2

OCCUPATIONAL

Learning to Learn

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Review local and foreign studies in the field of New Media. Creates innovative works in his/her field.
1
2
Criticize the effects of social media activities on socio-political field.
1

OCCUPATIONAL

Communication & Social

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Plan scientific studies in any area that can be encountered in different disciplines and transfer them to people from different disciplines.
3
2
Determine how much of the content produced by the media is right and wrong.
2

OCCUPATIONAL

Occupational and/or Vocational

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Follows the developments that have begun to guide the present and the future such as "Software". Produce various software products for different sectors.
1
2
Design using new architectures of big data processing systems.
5
3
Determine the logic of operation of artificial intelligence algorithms and determines the possible effects on media and indirectly society.
2

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT

Workload for Learning & Teaching Activities

Type of the Learning Activites Learning Activities (# of week) Duration (hours, h) Workload (h)
Lecture & In-Class Activities 14 3 42
Preliminary & Further Study 13 2 26
Land Surveying 0 0 0
Group Work 10 1 10
Laboratory 0 0 0
Reading 13 1 13
Assignment (Homework) 13 2 26
Project Work 1 30 30
Seminar 0 0 0
Internship 0 0 0
Technical Visit 0 0 0
Web Based Learning 0 0 0
Implementation/Application/Practice 0 0 0
Practice at a workplace 0 0 0
Occupational Activity 0 0 0
Social Activity 0 0 0
Thesis Work 0 0 0
Field Study 0 0 0
Report Writing 0 0 0
Final Exam 1 1 1
Preparation for the Final Exam 1 20 20
Mid-Term Exam 1 1 1
Preparation for the Mid-Term Exam 1 10 10
Short Exam 0 0 0
Preparation for the Short Exam 0 0 0
TOTAL 68 0 179
Total Workload of the Course Unit 179
Workload (h) / 25.5 7
ECTS Credits allocated for the Course Unit 7,0