Distributed Data Management - Interactive curriculae of TU Ilmenau

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module properties Distributed Data Management in degree program Master Informatik 2013 ATTENTION: not offered anymore
module number	200138
examination number	2200833
department	Department of Computer Science and Automation
ID of group	2254 (Databases and Information Systems)
module leader	Prof. Dr. Kai-Uwe Sattler
term	summer term only
language	Englisch
credit points	5
on-campus program (h)	34
self-study (h)	116
obligation	elective module
exam	written examination performance, 90 minutes
details of the certificate
link to Moodle course	https://moodle.tu-ilmenau.de/course/view.php?id=184
teacher	Prof. Dr. Kai-Uwe Sattler
signup details for alternative examinations
maximum number of participants
previous knowledge and experience	Lectures Advanced Database Systems and Transactional Information Systems
learning outcome	Nachdem Studierende diese Veranstaltung besucht haben, kennen sie die Prinzipien und Verfahren verteilter und paralleler Datenmanagementlösungen. Sie verstehen die Prinzipien dieser Techniken und können darauf aufbauend selbst Lösungen entwickeln. Die Studierenden können Techniken zur Anfrageverarbeitung, Replikation und Konsistenzsicherung erklären und hinsichtlich ihrer Vor- und Nachteile für verschiedene Einsatzzwecke bewerten. Sie sind in der Lage, verteilte und parallele Datenbanken zu entwerfen und aktuelle Datenbanktechnologien verteilter und paralleler Systeme zu bewerten und anzuwenden. Mit den Übungen können die Studierenden eigene Lösungen zu gestellten Aufgaben präsentieren, sich an themenspezifischen Diskussionen beteiligen und sind bereit, Fragen zu beantworten. _____________________________________________________________________________________________ After attending this class, students will be familiar with the principles and procedures of distributed and parallel data management solutions. They understand the principles of these techniques and can develop solutions based on them. Students will be able to explain techniques for query processing, replication, and data consistency, and evaluate their advantages and disadvantages for various application scenarios. They will be able to design distributed and parallel database management systems and evaluate and apply current database management system technologies for distributed and parallel systems. With the help of the seminars, students can present their own solutions to given tasks, participate in topic-specific discussions, and are prepared to answer questions.
content	Einführung und Motivation; Grundlagen verteilter Datenbanken: Architektur und Datenverteilung, verteilte Anfrageverarbeitung, Replikationsverfahren; Parallele Datenbanksysteme: Architektur und Datenverteilung, parallele Anfrageverarbeitung, Shared-Disk-Systeme; Web-Scale Data Mangement: SaaS und Multi Tenancy, Virtualisierungstechniken, Konsistenzmodelle, QoS, Partitionierung, Replikation, DHTs, MapReduce ___________________________________________________________________________________ - Introduction and motivation - Fundamentals of distributed databases Architecture and data distribution Distributed query processing Replication techniques - Parallel database systems Architecture and data distribution Parallel query processing Shared-Disk systems - Web-Scale Data Management SaaS and Multi-Tenancy Virtualization techniques Consistency models QoS Partitioning Replication DHTs MapReduce
media of instruction and technical requirements for education and examination in case of online participation	Vorlesung mit Präsentationen und Tafel, Handouts, Moodle
literature / references	Rahm, Saake, Sattler: Verteiltes und Paralleles Datenmanagement: Von verteilten Datenbanken zu Big Data und Cloud, Springer Vieweg, 2015 Lehner, Sattler: Web-Scale Data Management for the Cloud, Springer, 2013 M. Tamer Özsu, P. Valduriez: Principles of Distributed Database Systems, 3. Auflage, Springer, 2011
evaluation of teaching