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BDASEM Big Data Analytics Seminar

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#40353 / #10

SoSe 2023 - WiSe 2023/24

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

During the course of the seminar, the students will learn: (1) how to critically read and interpret scientific literature, (2) how to give a good scientific presentation that is technically precise, concentrated on the relevant topics, and also enjoyable, (3) how to summarize and write a critical, succinct technical review of a research paper. In addition, students will receive an introduction to contemporary research topics in data management, database systems, or technologies and systems for big data management and data science. Moreover, students will gain a great understanding of scientific publications, conferences, and the scientific review process.

Lehrinhalte

During the initial phase of this class, students will hear presentations on how to read and review scientific papers, and how to give a good presentation. Additionally, all participants will receive a raw submission version of a top-tier conference research paper. Task of the students is to critically read the paper and prepare a written review of the paper, following a typical conference reviewing template. Afterwards, students will receive the actual expert reviews of the paper, compare these to their findings, and prepare and deliver a presentation that discusses the improvements made between the original submission and the publication of the paper based on the reviewers' criticisms. Moreover, each week, students will be required to reflect on the main challenges addressed in each of their peers' presentations. (Details will be announced in the class.) Representative topics to be discussed, include data stream processing (e.g., scalable and parallel window joins, window aggregation, state management), data processing on modern hardware (e.g., GPU data processing, FPGA acceleration for data sketching), data processing for machine learning and data science (e.g., optimizing machine learning pipelines, dynamic parameter allocation in parameter servers), and query optimization and compilation (e.g., adaptive compilation).

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 students will receive an originally submitted conference paper. Then each student should identify and use secondary sources to further investigate the assigned topic. A few weeks afterwards students will prepare a written review of their paper adhering to the scientific reviewing standards. At the end of the semester, each student will offer a presentation, as well as a discussion of all of the other seminar papers. 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 third semester Master's students with a focus on database systems and information management. Desirable prerequisites include the following: (a) successfully completed the TU Berlin Database Technology (DBT) course or its equivalent, (b) at least one of the advanced information management courses, such as the Management of Data Streams or Data Management on Modern Hardware, (c) sound understanding of written and spoken English. Ideally, this seminar should be taken the semester before commencing your master's thesis.

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) Discussion of Seminar Content30mündlich3-5 minutes discussion per paper
(Deliverable Assessment) Seminar Presentation40mündlich20 minutes
(Deliverable Assessment) Written Paper Review30schriftlich3-5 pages

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'. See the table above for details. The final grade according to § 68 (2) AllgStuPO will be calculated with the faculty grading Table 2. (Die Gesamtnote gemäß § 68 (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 8.

Anmeldeformalitäten

Students are required to register for the course in the official TUB examination system within six weeks after commencement of the first lecture or when the first graded assignment is due, whichever happens to be first.

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 course targets Master's students interested in database systems and information management. This seminar is one of eligible courses for those following the Fak. IV Data Science and Engineering Track: https://www.tu.berlin/en/dima/analytics/data-science-and-engineering-track.

Sonstiges

Keine Angabe