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Data Management in the Cloud - Einzelansicht

Grunddaten
Veranstaltungsart Vorlesung Kurztext
Veranstaltungsnummer INF-12820-20131 Rhythmus
Semester SS 2013 Studienjahr
Erwartete Teilnehmer/-innen 20 Max. Teilnehmer/-innen 50
SWS 3 Sprache englisch
Credits 5
Hyperlink http://www.informatik.uni-konstanz.de/grossniklaus/education/clouddb/
Belegungsfrist
Termine: Vorlesung iCalendar Export
  Tag Zeit Rhythmus Dauer Raum Raum-
plan
Lehrperson Status Bemerkung fällt aus am Max. Teilnehmer/-innen
Einzeltermine anzeigen
iCalendar Export
Mi. 08:15 bis 09:45 wöchentl. 17.04.2013 bis 17.07.2013  C - C 336 $lang.rollstuhl_gelb      
Vorlesung:
 
Termine: Übung iCalendar Export
  Tag Zeit Rhythmus Dauer Raum Raum-
plan
Lehrperson Status Bemerkung fällt aus am Max. Teilnehmer/-innen
Einzeltermine anzeigen
iCalendar Export
Fr. 11:45 bis 13:15 wöchentl. 19.04.2013 bis 19.07.2013  R - R 511      
Übung:
 


Dozent/in
Dozent/in Zuständigkeit
Grossniklaus, Michael, Jun.-Prof. Dr. verantwortlich
StudIS-Prüfungen / Module
Prüfungsnummer Prüfungstext
INF-12820 Data Management in the Cloud
StudIS-Prüfungsorganisationssätze
Semester Termin Prüfer/-in Datum Beginn Dauer Raum Bemerkung Leistungsanmeldung Rücktritt bis StudIS-
Status
SS 2013 02 Grossniklaus, Michael , Juniorprof. Dr. 14.10.2013 Nicht/noch nicht für die StudIS-Prüfungsanmeldung freigeschaltet
SS 2013 01 Grossniklaus, Michael , Juniorprof. Dr. 31.07.2013 15.04.2013 bis
15.05.2013
28.06.2013 StudIS-Prüfungsanmeldung beendet
_______________
Nicht/noch nicht für die StudIS-Prüfungsanmeldung freigeschaltetNicht/noch nicht für die StudIS-Prüfungsanmeldung freigeschaltet
Für die StudIS-Prüfungsanmeldung freigeschaltet - Prüfungsanmeldung läuft noch nichtFür die StudIS-Prüfungsanmeldung freigeschaltet - Prüfungsanmeldung läuft noch nicht
Für die StudIS-Prüfungsanmeldung freigeschaltet - Prüfungsanmeldung läuft derzeitFür die StudIS-Prüfungsanmeldung freigeschaltet - Prüfungsanmeldung läuft derzeit
Anmeldezeitraum abgelaufen - Rücktritt noch möglichAnmeldezeitraum abgelaufen - Rücktritt noch möglich
StudIS-Prüfungsanmeldung beendetStudIS-Prüfungsanmeldung beendet
Zuordnung zu Einrichtungen
FB Informatik und Informationswissenschaft
LS Datenbanken und Informationssysteme
Inhalt
Literatur

The following study material and literature is available and relevant for this course.

  • Course slides: Copies of the slide decks used in the lecture as well as hand-outs for the exercises and reading assignments that accompany the course will be available online.
  • Reading list: A bibliography of the references used in the course as well as further readings will be available on the course website
Voraussetzungen

The following skills, knowledge and courses are mandatory prerequisites to attend and successfully complete this course.

  • Basics of database systems: database design, query languages, database application programming, etc. (INF-12040 or equivalent)
  • Principles of database systems: relational model, relational algebra, normal forms, etc. (INF-12040 or equivalent)
  • Computer systems: computer architecture, operating systems, networks, etc. (INF-11740, INF-11880, or equivalent)
  • System programming: students must have the ability to program in a language appropriate for system implementation, such as C/C++, C# or Java. (INF-11930 or equivalent)
  • Key competences: Subversion, LaTeX, etc. (INF-10175 or equivalent)
Leistungsnachweis

Depending on the number of participants, there will be an oral exam (up to 30 students) or a written exam (more than 30 students). The type of exam will be announced in the first week of the course. Reading assignments and a practical project are an integral part of the lecture and will contribute 50% of the final grade. The reading assignments will be weighted as 20% and the project as 30%.

Lerninhalte

Cloud computing has recently seen a lot of attention from research and industry for applications that can be parallelized on shared-nothing architectures and have a need for elastic scalability. As a consequence, new data management requirements have emerged with multiple solutions to address them. This course will look at the principles behind data management in the cloud as well as discuss actual cloud data management systems that are currently in use or being developed. The topics covered in the course range from novel data processing paradigms (MapReduce, PigLatin, Hive), to commercial cloud data management platforms (Google AppEngine, Microsoft Windows Azure, Amazon Web Services) and open-source NoSQL databases (Cassandra, MongoDB, Neo4j). The world of cloud data management is currently very diverse and heterogeneous. Therefore, our course will also report on efforts to classify, compare and benchmark the various approaches and systems. Students in this course will gain broad knowledge about the current state of the art in cloud data management and, through a course project, practical experience with a specific system.

Zielgruppe

The course targets the following groups of students.

  • Advanced Bachelor students in Computer Science or Information Engineering, who are close to graduation and meet the mandatory minimum requirements for this course
  • Master students in Information Engineering, who meet the mandatory minimum requirements
  • All students, who meet the minimum requirements for this course and who plan to specialize in the area of databases and information systems by conducting a project or attending a practical course on this topic
Lernziel

The syllabus of this course aims at empowering students to follow and understand current trends in cloud computing and how they impact data management systems. Based on the acquired knowledge students will be capable to critically assess and differentiate between novel and emerging cloud data management systems. In particular, the learning content of this course will improve the students’ ability to relate the requirements and characteristics of applications to the features and functionality of cloud data management systems. In an increasingly heterogeneous market of data management systems, the skill to make these informed choices is a key competence of graduates in computer science.

Arbeitsaufwand

150 hours, of which ca. 50 hours are spent in class and another 100 hours are spent on assignments and the course project. Since cloud data management is a relatively new field, self-study and practical exercises are an integral part of this course. Therefore, these activities will take up 66% of the amount of work and will have an influence of 50% on the final grade.


Strukturbaum
Keine Einordnung ins Vorlesungsverzeichnis vorhanden. Veranstaltung ist aus dem Semester SS 2013 , Aktuelles Semester: SS 2017
STUDIS    Anzahl aktueller Nutzer/-innen: 75 Haben Sie Anregungen, Fragen, Lob oder Kritik zum LSF?
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