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BDASEM - Big Data Analytics Seminar

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SS 2014 - SS 2015

English

BDASEM - Big Data Analytics Seminar

3

Markl, Volker

Benotet

Portfolioprüfung

English

Zugehörigkeit


Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34351500 FG Datenbanksysteme und Informationsmanagement (DIMA)

Keine Angabe

Kontakt


EN 7

Soto, Juan

sekr@dima.tu-berlin.de

https://www.tu.berlin/dima

Lernergebnisse

Participants of this seminar will acquire knowledge about recent research results and trends in the analysis of web-scale data. Through the work in this seminar, students will learn the comprehensive preparation and presentation of a research topic in this field. In order to achieve this, students will get to read and categorise a scientific paper, conduct background literature research and present as well as discuss their findings. After the course, students will be able to critically read and evaluate scientific publications, and to conduct background research. They will be capable of preparing for and giving oral presentations on research topics for an expert audience, of analyzing the state of the art of a research topic, and of summarizing it in a scientific paper. They should also understand techniques used in the scientific community like peer reviews, conference presentations, and defenses of the findings after their presentation, as well as they should understand methods for large-scale data analytics. The course is principally designed to impart: Technical skills: 50x Methodological skills: 20x System skills: 10x Social skills: 20x

Lehrinhalte

Both the sciences and industry are currently undergoing a profound transformation: largescale, diverse data sets - derived from sensors, the web, or via crowd sourcing - present a huge opportunity for data-driven decision making. This data poses new challenges in a variety of dimensions: in its unprecedented volume, in the speed at which it is generated (its velocity) and in the variety of data sources that need to be integrated. A whole new breed of systems and paradigms is currently developed to be able to cope with that these challenges. The field of Big Data Analytics deals with the technological means of gaining insights from huge amounts of data. In this seminar, students will review the current state of the art in this field. At the beginning of the semester you will receive a set of primary literature, which consists of a basic item for every participant. Then you will learn about presentation techniques and guidelines on how to read scientific papers. This is be extended by learning how to write texts specially in the context of the English language. Then you should use secondary sources to research your topic assigned to you in the seminar, which should go beyond the supplied primary literature. Next to conventional sources like the internet you are required to use research journals and articles published at information management conferences such as WWW, VLDB, or SIGMOD.

Modulbestandteile

Compulsory area

Die folgenden Veranstaltungen sind für das Modul obligatorisch:

LehrveranstaltungenArtNummerTurnusSpracheSWS ISIS VVZ
BDASEM - Big Data Analytics SeminarSEM0434 L 477WiSeKeine Angabe2
ISIS-Kurssuche nach Veranstaltungen des Moduls

Arbeitsaufwand und Leistungspunkte

BDASEM - Big Data Analytics Seminar (SEM):

AufwandbeschreibungMultiplikatorStundenGesamt
Präsenzzeit15.02.0h30.0h
Vor-/Nachbereitung15.04.0h60.0h
90.0h(~3 LP)
Der Aufwand des Moduls summiert sich zu 90.0 Stunden. Damit umfasst das Modul 3 Leistungspunkte.

Beschreibung der Lehr- und Lernformen

About four weeks after receiving the primary literature you will have to give a short presentation which should last about 10 minutes. The presented topic will then be discussed for about 10 minutes by the seminar group. This is done so that the other seminar participants can give you constructive feedback about the content of your talk. At the end of the semester you will have to give another talk which should be about 30 minutes long. In addition to the talk you will also have to hand in a 10 page report describing and evaluating the topic.

Voraussetzungen für die Teilnahme / Prüfung

Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen:

This course is aimed at master students with a focus on database systems and information management and should be chosen after the 2nd semester. To be able to participate you must have successfully completed IDB and AIM. In the ideal case this seminar should be taken by students who are directly in front of their master thesis or have already completed it and are interested in a doctorate in information management.

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung:

Dieses Modul hat keine Prüfungsvoraussetzungen.

Abschluss des Moduls

Benotung

Benotet

Prüfungsform

Portfolio examination

Art der Portfolioprüfung

Keine Angabe

Sprache(n)

English

Prüfungselemente

NamePunkte/GewichtKategorieDauer/Umfang
presentation50Keine AngabeKeine Angabe
written seminar report50Keine AngabeKeine Angabe

Notenschlüssel

Keine Angabe

Dauer des Moduls

Für Belegung und Abschluss des Moduls ist folgende Semesteranzahl veranschlagt:
1 Semester.

Dieses Modul kann in folgenden Semestern begonnen werden:
Wintersemester.

Maximale teilnehmende Personen

Die maximale Teilnehmerzahl beträgt 16.

Anmeldeformalitäten

Students are required to register via the DIMA course registration tool before the start of the first lecture (http://www.dima.tu-berlin.de/). Within the first six weeks after commencement of the lecture, students will have to register for the course at QISPOS (university examination protocol tool) and ISIS (course organization tool) in addition to the registration at the DIMA course registration tool.

Literaturhinweise, Skripte

Skript in Papierform

Verfügbarkeit:  nicht verfügbar

 

Skript in elektronischer Form

Verfügbarkeit:  nicht verfügbar

 

Literatur

Empfohlene Literatur
Will be released at the beginning of the seminar.

Zugeordnete Studiengänge


Diese Modulversion wird in folgenden Studiengängen verwendet:

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Dieses Modul findet in keinem Studiengang Verwendung.

Studierende anderer Studiengänge können dieses Modul ohne Kapazitätsprüfung belegen.

Wahlpflichtmodul im Masterstudiengang Wirtschaftingenieurswesen (Studiengang IuK).

Sonstiges

Keine Angabe