BDA5012 Big Data in Cloud ComputingBahçeşehir UniversityDegree Programs BIG DATA ANALYTICS AND MANAGEMENT (ENGLISH, NONTHESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
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
BDA5012 Big Data in Cloud Computing Fall 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 : Dr. Öğr. Üyesi SERKAN AYVAZ
Course Objectives: The objective of this course is to introduce students with essential concepts of Cloud Computing and how to use them in Big Data.

Learning Outcomes

The students who have succeeded in this course;
1) Understand Current Cloud Computing Technologies such as Virtual Machines, SAAS, IAAS, Cloud Based Networks, Cloud Based Databases
2) Understand and articulate how to use and develop products on Cloud Computing Systems
3) Develop skills to analyse problems to create solutions using Cloud Computing and integrate this solution to Big Data Systems.

Course Content

The course will cover topics in architectures, features, and benefits of Cloud Computing; Cloud Computing technologies such as Virtual Machines, SAAS, IAAS, Cloud Based Networks, Cloud Based Databases.
Describe Cloud Computing solutions, and identify parameters for managing and monitoring big data infrastructure.
Scenarios using sample data will be conducted, to develop skills using Cloud Computing Infrastructure.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Course structure, resources, Cloud Computing concepts and scenarios
2) Virtual Machines and Understanding with the Code library, SDKs, and IDE toolkits
3) Service object models and baseline concepts for working with storage systems and Databases
4) Service object models for Notification and Queue Services
5) Understanding Security and Applying security features
6) Application Development and Deployment Best Practices
7) Distributed Environments
8) Event Driven Scaling
9) Orchestrating Batch Processing
10) Large Scale Design Patterns
11) Case Study 1
12) Case Study 2
13) Projects presentations
14) Project presentations

Sources

Course Notes / Textbooks: Ders Notları, Referans Kaynaklar, Referans Kitaplar
References: Cloud Computing: Concepts, Technology & Architecture,Thomas Erl,Prentice Hall
Cloud Computing: Theory and Practice,Dan C. Marinescu,
The Great Cloud Migration: Your Roadmap to Cloud Computing, Big Data and Linked Data ,Michael C. Daconta

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Project 1 % 20
Midterms 1 % 30
Final 1 % 50
Total % 100
PERCENTAGE OF SEMESTER WORK % 30
PERCENTAGE OF FINAL WORK % 70
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