CLOUD DATA MANAGEMENT
- Overview
- Assessment methods
- Learning objectives
- Contents
- Full programme
- Delivery method
- Teaching methods
- Contacts/Info
The course requires that students have good knowledge of relational data management systems.
The exam consists of a written exam of 2 hours in which the student is required to respond to open questions, aimed at verifying the acquisition and proper understanding of the topics presented during the course. The final vote, out of thirty, will take into account the accuracy and quality of the responses (70%), the skill of exposure (10%) and the ability to adequately justify statements, analyzes and opinions (20%).
The course aims at providing the necessary knowledge and skills needed for the design and use of data management systems in cloud computing. After having attended the course, the student will be able to autonomously judge the services provided by cloud frameworks, to design new cloud-based solutions by taking into account current ICT standards, when available.
The course aims to
1- provide basic concepts related to cloud computing, cloud service models and cloud infrastructure deployment models.
2- train the student to the use of cloud computing enabling technologies.
3- initiate the student to the main paradigms for data analysis in the cloud
4- introduce data management systems for the cloud
5- analyze security and privacy issues of cloud data management.
The studied topics will be presented, where possible, by taking as reference the architectures of the principal commercial solutions (e.g., Microsoft, Amazon web service, etc.).
In addition, the course aims to develop in the student soft skills, such as the ability to autonomously learn new cloud data management technologies. It is expected that, after attending this course, the student will be able to assess the strengths and weaknesses of cloud data management technologies.
- Foundations of cloud computing (goal 1, Lectures 4h)
--The cloud model and its properties
--Service models for cloud computing
--Deployment models for cloud infrastructures
- Enabling technologies (goal 2, Lectures 10h -- 6h theory, 4h labs)
-- Introduction to virtualization
-- Containerization and orchestration
- Data management and analysis in the cloud (goal 3, Lectures 32h -- 12 h theory, 10 h exercise, 10h labs)
--Distributed computational paradigm
-Cloud-based NoSQL databases (goal 4, Lectures 10h -- 6 h theory, 2 h exercise, 2h labs)
--System families, data models and query languages
- Privacy and security issues (goal 5, Lectures 4h)
--Data protection techniques
See section Contents.
The course is composed of lessons (32 hours), exercise sessions (12 hours), and laboratory sessions (16h), as illustrated in the Course Content section of this syllabus.
Professor Office hours: by appointment.
Send an e-email to pietro.colombo@uninsubria.it from students’ official uninsubria e-mail.
Professors
Borrowers
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Degree course in: COMPUTER SCIENCE