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Data Management in Large-Scale Distributed Systems
# =74QS Subject Rankings
12 monthsProgram duration
243 EURTuition Fee/year
YesScholarships
Program overview
Main Subject
Computer Science and Information Systems
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Read more with a precise understanding of the technological and scientific challenges involved in the design of these new architectures and the development of Big Data applications using them. The complexity, heterogeneity, and distribution of data and processing must be taken into account as much as the reliability, security, and performance of the underlying data managers (RDBMS or NoSQL).
The skills acquired at the end of the programme follow three axes:
1) big data architectures, cloud and IoT, security and performance;
2) data integration and quality, data mining and knowledge extraction;
3) development and deployment of data-driven services and applications.
Students receive a common core curriculum along these three axes. This common core is supplemented by optional courses covering various topics such as data mining, data confidentiality, the semantic web, cloud computing, ambient data management, the Internet of Things or application development frameworks, opening up research perspectives associated with these different topics.
In order to apply to one of the programmes of the master, please select the programme you are interested in under the "Year 1 & 2 Master's programmes" tab . Read less
Program overview
Main Subject
Computer Science and Information Systems
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Read more with a precise understanding of the technological and scientific challenges involved in the design of these new architectures and the development of Big Data applications using them. The complexity, heterogeneity, and distribution of data and processing must be taken into account as much as the reliability, security, and performance of the underlying data managers (RDBMS or NoSQL).
The skills acquired at the end of the programme follow three axes:
1) big data architectures, cloud and IoT, security and performance;
2) data integration and quality, data mining and knowledge extraction;
3) development and deployment of data-driven services and applications.
Students receive a common core curriculum along these three axes. This common core is supplemented by optional courses covering various topics such as data mining, data confidentiality, the semantic web, cloud computing, ambient data management, the Internet of Things or application development frameworks, opening up research perspectives associated with these different topics.
In order to apply to one of the programmes of the master, please select the programme you are interested in under the "Year 1 & 2 Master's programmes" tab . Read less
Admission Requirements
- Certificate of French (compulsory for non-French speakers).
- Motivation letter.
- Curriculum Vitae.
- All transcripts of the years / semesters validated since the high school diploma at the date of application.
Additional supporting documentsTuition Fee and Scholarships
Domestic Students
International Students
One of the important factors when considering a master's degree is the cost of study. Luckily, there are many options available to help students fund their master's programme. Download your copy of the Scholarship Guide to find out which scholarships from around the world could be available to you, and how to apply for them.
In this guide you will find:
Where to look for scholarship opportunities
How to apply to scholarships relevant to you
A list of available scholarships around the world
A scholarship application checklist
QS subject rankings
Subject: Computer Science and Information Systems
Ranking criteria
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