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BDASEM - Big Data Analytics Seminar

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WS 2018/19 - WiSe 2020/21

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 students will receive a set of primary literature, which consists of basic reading material for every participant. Students will review this material under the guidance of a mentor. At the same time, students will learn about presentation techniques, techniques for critical reading of scientific papers, as well as scientific writing. Students will use secondary literature to research the assigned topic assigned, including 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 477WiSe/SoSeen2
ISIS-Kurssuche nach Veranstaltungen des Moduls

Arbeitsaufwand und Leistungspunkte

BDASEM - Big Data Analytics Seminar (SEM):

AufwandbeschreibungMultiplikatorStundenGesamt
Plenary sessions15.02.0h30.0h
Preparation/Individual work15.04.0h60.0h
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

At the beginning of the semester you will receive a set of primary literature. Then you should find and use secondary sources to investigate the topic assigned to you in the seminar, which should go beyond the supplied primary literature. A few weeks after receiving the primary literature you will have to give a short presentation of approx. 10 minutes. The presented topic will be discussed by the other seminar participants in order to give you constructive feedback about the content of your talk. In the further course of the semester you will have to give a long final presentation of approx. 30 minutes. In addition to the talk you will also have to hand in a 10-15 page technical report describing and evaluating your topic. Details may vary and will be announced in the respective semester.

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 master semester. To be able to participate you should have successfully completed 'Database Technology DBT' and one of the 'Advanced Information Management AIM' (1,2,3) courses. 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. It is vital that you have a sound understanding of written and spoken English.

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung:

Dieses Modul hat keine Prüfungsvoraussetzungen.

Abschluss des Moduls

Benotung

Benotet

Prüfungsform

Portfolio examination

Art der Portfolioprüfung

100 Punkte insgesamt

Sprache(n)

English

Prüfungselemente

NamePunkteKategorieDauer/Umfang
(Deliverable assessment) long written seminar report40schriftlich10-15 pages
(Deliverable assessment) presentation 120mündlich20 min
(Deliverable assessment) presentation 230mündlich30 min.
(Deliverable assessment) short written seminar report/s10schriftlich4-6 pages in total

Notenschlüssel

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl1.01.31.72.02.32.73.03.33.74.0
100.0pt95.0pt90.0pt85.0pt80.0pt75.0pt70.0pt65.0pt60.0pt55.0pt50.0pt

Prüfungsbeschreibung (Abschluss des Moduls)

The exam will be done as a 'portfolio examination', including two deliverable assessments, totaling for 100 portfolio points: - 2 seminar presentations (50 portfolio points) - 2 written seminar reports (50 portfolio points) Cf. the details in the resp. fields, and follow the instructions in the beginning of the class. The final grade according to § 47 (2) AllgStuPO will be calculated with the faculty grading table 2. (Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt.)

Dauer des Moduls

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

Dieses Modul kann in folgenden Semestern begonnen werden:
Winter- und Sommersemester.

Maximale teilnehmende Personen

Die maximale Teilnehmerzahl beträgt 16.

Anmeldeformalitäten

For registration to this module, please apply to DIMA following the guidelines in the DIMA web site: https://www.dima.tu-berlin.de/menue/studium_und_lehre/parameter/en/

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.
This module is mandatory for the Erasmus Mundus IT4BI master program, and it is mandatory elective for the EIT-Digital Data Science Master.

Sonstiges

Keine Angabe