Big data infrastructures
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Teaching
Details
Faculty Faculty of Science and Medicine Domain Computer Science Code UE-SIN.07612 Languages English Type of lesson Lecture
Level Master Semester SA-2020 Schedules and rooms
Summary schedule Wednesday 14:15 - 17:00, Hebdomadaire (Autumn semester)
Struct. of the schedule 3h par semaine durant 14 semaines Contact's hours 42 Teaching
Responsibles - Cudré-Mauroux Philippe
Teachers - Cudré-Mauroux Philippe
Assistants - Bhardwaj Akansha
- Rosso Paolo
Description This course focuses on conceptual and architectural issues related to the design and deployment of modern data management infrastructures in a Big Data context. It starts with a review of distributed transaction processing techniques, classical parallel databases systems and ACID-style semantics in shared-nothing architectures. The course then delves into modern wide-area data processing, with an emphasis on recent systems developed to solve large-scale problems using clusters of commodity machines. In this second part, the course covers distributed storage systems (such as Google's BigTable), wide-area hash-tables (like Cassandra), data-intensive computing platforms (Hadoop) and nosql systems. Hands on programming exercises using those platforms will be an important part of this course. Training objectives Students will learn about classical distributed transaction processing and parallel database systems. They will get exposed to modern data management infrastructures deployed by current Web giants like Google or Yahoo! to power a wide range of Web services. Finally, they will understand the fundamental tradeoffs between consistency, availability and fault-tolerance for wide-area data processing on the Internet. Comments MSc-CS BENEFRI - (Code Ue: 63021 / Tracks: T6)
The exact date and time of this course as well as the full course list can be found under http://diuf.unifr.ch/drupal/mcs/program/courses-timetable/courses.Softskills No Off field No BeNeFri Yes Mobility Yes UniPop No -
Dates and rooms
Date Hour Type of lesson Place 16.09.2020 14:15 - 17:00 Cours PER 21, Room G120 23.09.2020 14:15 - 17:00 Cours PER 21, Room G120 30.09.2020 14:15 - 17:00 Cours PER 21, Room G120 07.10.2020 14:15 - 17:00 Cours PER 21, Room G120 14.10.2020 14:15 - 17:00 Cours PER 21, Room G120 21.10.2020 14:15 - 17:00 Cours PER 21, Room G120 28.10.2020 14:15 - 17:00 Cours PER 21, Room G120 04.11.2020 14:15 - 17:00 Cours PER 21, Room G120 11.11.2020 14:15 - 17:00 Cours PER 21, Room G120 18.11.2020 14:15 - 17:00 Cours PER 21, Room G120 25.11.2020 14:15 - 17:00 Cours PER 21, Room G120 02.12.2020 14:15 - 17:00 Cours PER 21, Room G120 09.12.2020 14:15 - 17:00 Cours PER 21, Room G120 16.12.2020 14:15 - 17:00 Cours PER 21, Room G120 -
Assessments methods
Written exam
Assessments methods By rating -
Assignment
Valid for the following curricula: Additional Courses in Sciences
Version: ens_compl_sciences
Paquet indépendant des branches > Specialized courses in Computer Science (Master level)
Additional programme requirements for PhD studies [PRE-DOC]
Version: 2020_1/v_01
Additional programme requirements for PhD studies (Faculty of Science and Medicine) > Specialized courses in Computer Science (Master level)
Computer Science [3e cycle]
Version: 2015_1/V_01
Continuing education > Specialized courses in Computer Science (Master level)
Computer Science [POST-DOC]
Version: 2015_1/V_01
Continuing education > Specialized courses in Computer Science (Master level)
MSc in Computer science (BeNeFri)
Version: 2023_1/V_01
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Version: 2020/SA_V02
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Ma - Business Informatics - 90 ECTS
Version: 2020/SA-v01
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Version: 2019/SA_V01
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Version: 2020/SA_V01
Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for DigitalizationCours > Module Informatik > Data Science
MiMa - Data Analytics - 30 ECTS
Version: 2020/SA-v01
À choix 9 crédits ECTS > TMD: Technologies and Modelling for DigitalizationÀ choix 9 crédits ECTS > Data Science