Big data infrastructures

  • 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
    MSc in Computer science (BeNeFri), lectures, seminars and Master thesis > T6: Data Science

    Ma - Business Communication : Business Informatics - 90 ECTS
    Version: 2020/SA_V02
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization
    Courses - 60 ECTS > Option Group > Information Management > Cours > Module Informatik > Data Science

    Ma - Business Informatics - 90 ECTS
    Version: 2020/SA-v01
    Classes - min. 45 ECTS > Modules IT Management - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization
    Classes - min. 45 ECTS > Module IT and IT Management > TMD: Technologies and Modelling for Digitalization
    Classes - min. 45 ECTS > Module IT and IT Management > Data Science

    MiMa - Business Informatics - 30 ECTS
    Version: 2020/SA_V01
    Cours > Module Wirtschaftsinformatik > TMD: Technologies and Modelling for Digitalization
    Cours > Module Informatik > Data Science

    MiMa - Data Analytics - 30 ECTS
    Version: 2020/SA-v01
    À choix 9 crédits ECTS > TMD: Technologies and Modelling for Digitalization
    À choix 9 crédits ECTS > Data Science